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Conferences, Lectures, & Seminars
Events for March
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Seminar in Biomedical Engineering
Mon, Mar 02, 2015 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Adriana Nicholson, BME PhD Candidate, Medical Device Development Facility (Loeb Lab)
Talk Title: Electronics Design and In Vivo Evaluation of a Wirelessly Rechargeable Fetal Micropacemaker
Abstract: A miniaturized, self-contained pacemaker that could be implanted with a minimally invasive technique would dramatically improve the survival rate for fetuses that develop hydrops fetalis as a result of congenital heart block. We are currently validating a device that we developed to address this clinical need. Preclinical studies are underway to demonstrate that the device can be implanted via a minimally invasive approach, can induce effective contractions of the heart muscle with an adequate safety factor, and can successfully operate for the required device lifetime of three months using the previously-developed closed loop transcutaneous recharging system. I will present our progress in realizing the implant system and a method that we developed to evaluate the quality of each implantation in real time.
Host: Stanley Yamashiro
Location: OHE 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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CS Colloquium: Sergey Levine (UC Berkeley) - Deep Learning for Decision Making and Control
Tue, Mar 03, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sergey Levine, UC Berkeley
Talk Title: Deep Learning for Decision Making and Control
Series: CS Colloquium
Abstract: A remarkable feature of human and animal intelligence is the ability to autonomously acquire new behaviors. My work is concerned with designing algorithms that aim to bring this ability to robots and simulated characters. A central challenge in this field is to learn behaviors with representations that are sufficiently general and expressive to handle the wide range of motion skills that are necessary for real-world applications, such as general-purpose household robots. These representations must also be able to operate on raw, high-dimensional inputs and outputs, such as camera images, joint torques, and muscle activations. I will describe a class of guided policy search algorithms that tackle this challenge by transforming the task of learning control policies into a supervised learning problem, with supervision provided by simple, efficient trajectory-centric methods. I will show how this approach can be applied to a wide range of tasks, from locomotion and push recovery to robotic manipulation. I will also present new results on using deep convolutional neural networks to directly learn policies that combine visual perception and control, learning the entire mapping from rich visual stimuli to motor torques on a real robot. I will conclude by discussing future directions in deep sensorimotor learning and how advances in this emerging field can be applied to a range of other areas.
The lecture will be streamed through the dedicated link HERE.
Biography: Sergey Levine is a postdoctoral researcher working with Professor Pieter Abbeel at UC Berkeley. He completed his PhD in 2014 with Vladlen Koltun at Stanford University. His research focuses on robotics, machine learning, and computer graphics. In his PhD thesis, he developed a novel guided policy search algorithm for learning rich, expressive locomotion policies. In later work, this method enabled learning a range of robotic manipulation tasks, as well as end-to-end training of policies for perception and control. He has also developed algorithms for learning from demonstration, inverse reinforcement learning, and data-driven character animation.
Host: Computer Science Department
More Info: https://bluejeans.com/658994068
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/658994068
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Epstein ISE Department Seminar
Tue, Mar 03, 2015 @ 10:00 AM - 11:00 AM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Phebe Vayanos, Lecturer and Postdoctoral Associate, MIT Operations Research Center
Talk Title: Data-Driven Learning Under Uncertainty: An Adaptive Optimization Perspective
Abstract: Motivated by the recent explosion of data availability and the plethora of decision problems affected by uncertainty, we propose a data-driven paradigm for dynamic learning that unifies optimization and estimation. Our framework naturally captures the critical exploration-exploitation trade-off of the decision-maker, and we develop a tractable solution scheme to compute near-optimal policies. We showcase the versatility of our method by applying it to two very diverse areas: we focus on a pricing problem arising in revenue management and then discuss an application in energy.
In the area of revenue management, we discuss the pricing problem faced by a retailer who has a finite inventory of a product available for sale. We assume that the product demand curve is unknown to the retailer who has at his disposal a history of sales data. We present computational results that show that our proposed policies: (a) yield higher profits compared to commonly used policies, (b) nearly match results obtained with perfect information under downside measures such as Conditional Value-at-Risk, and (c) can be obtained in modest computational time for large-scale problems.
In the area of energy, we discuss an industrial application of our research in collaboration with BP, one of the worldâs major oil and gas companies. Using actual data from a BP oilfield, we create a simple and powerful model for predicting oil production that circumvents the need for complex reservoir modeling. We leverage this model and the framework described above to devise a methodology that enables oil companies to maximize the quantities of oil extracted from each reservoir, and therefore decrease the natural resources (and energy supplies) that are left untapped.
This is joint work with Dimitris Bertsimas, MIT.
Biography: Phebe Vayanos is a lecturer in the Operations Research and Statistics Group at MIT Sloan School of Management, and a postdoctoral research associate in the Operations Research Center at MIT. Her current research is focused on developing data-driven models and scalable solution approaches for real-world decision problems affected by uncertainty and ambiguity. In particular, she is motivated by applications in revenue management, energy, finance, education, and healthcare. She holds a PhD degree in Operations Research and an MEng degree in Electrical & Electronic Engineering, both from Imperial College London. She has extensive experience with the energy and investment banking industries, having worked at JPMorgan and BNP Paribas and having consulted for BP.
More Information: SEMINAR-Vayanos.doc
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Epstein Institute / ISE 651 Seminar Series
Tue, Mar 03, 2015 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Alejandro Toriello, Assistant Professor, H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology
Talk Title: The One-Dimensional Dynamic Dispatch Waves Problem
Series: Epstein Institute Seminar Series
Abstract: We study same-day delivery distribution systems by formulating the Dynamic Dispatch Waves Problem (DDWP), which models a depot where delivery requests arrive dynamically throughout a service day. At any dispatch epoch (wave), the information available to the decision maker is (1) a set of known, open requests which remain unfulfilled, and (2) a set of potential requests that may arrive later in the service day; the decision maker decides whether or not to dispatch a vehicle at each wave, and if so, which subset of open requests to serve, with the objective of minimizing expected vehicle operating costs and penalties for unserved requests. We consider the DDWP with a single delivery vehicle and request destinations on a line: We describe a class of a priori dispatch policies that plan routes for each wave in advance, and provide a dynamic programming approach for determining an optimal policy of this kind. We then discuss the benefits of dynamic policies, and propose several bounds and heuristics for the dynamic case.
Joint work with Alan Erera and Mathias Klapp
Biography: Alejandro Toriello joined Georgia Tech ISyE in August 2013 as an assistant professor. His research interests lie in the theory and application of supply chain management, logistics and transportation, and in related optimization methodologies. He currently serves as associate editor for the journals Optimization Methods and Software and Transportation Science. Prior to joining ISyE, he served as an assistant professor in the Epstein Department of Industrial and Systems Engineering at the University of Southern California.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Information: Seminar-Toriello2.docx
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Communications, Networks & Systems (CommNetS) Seminar
Wed, Mar 04, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Kangwon Lee, Korea Polytechnic University
Talk Title: Longitudinal Driver Models & Driving Databases
Series: CommNetS
Abstract: This presentation will talk about how people drive their cars. More specifically about accel / brake pedals: the longitudinal human driver models and numerical evaluation of them using naturalistic human driving databases. First, driver model, car following situation and naturalistic driving databases will be described. Then longitudinal driver models and a evaluation configuration will be presented. Finally the Modified Gipps Model showing the best performance of the presented models will be analyzed more in detail and compared with real traffic flow rate data.
Biography: Kangwon Lee is an Associate Professor in Mechanical Engineering at the Korea Polytechnic University. He received his Ph. D. in Mechanical Engineering from the University of Michigan, Ann Arbor in 2004. His research interests cover ground vehicle control systems including automotive active safety and driver assistant systems.
Host: Prof. Ashutosh Nayyar and the Ming Hsieh Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Aerospace and Mechanical Engineering Seminar Series
Wed, Mar 04, 2015 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Xianyi Zeng, Postdoctoral Associate in the Department of Civil and Environmental Engineering at Duke University, Durham, NC
Talk Title: Multi-Robot Systems for Monitoring and Controlling Large Scale Environments A Variational Multiscale Finite Element Method for Nearly Incompressible Solids and Fluid-Structure Interactions
Series: Aerospace and Mechanical Engineering Seminar Series
Abstract: We present a new approach to stabilize the finite element methods for explicit transient solid mechanics in the nearly incompressible regime using linear simplicial finite elements, and present its extension to fluid-structure interactions. In these problems, triangular/tetrahedral elements are usually preferred because they allow efficient and automated mesh generation for complicated geometries. However, standard Galerkin formulation typically leads to volume locking or instability on these elements in the case of nearly incompressible solid dynamics.
To overcome these difficulties, we describe a stabilized method that is based on a mixed formulation, in which the usual momentum equation is complemented by a rate equation for the evolution of the pressure field. The stabilization term is derived using a variational multiscale approach for isotropic linear elastic materials, and it is shown to greatly improve the stability of the methods without decreasing the order of the accuracy. Next we extend the methodology to nonlinear elastic materials by properly linearizing the variational form, and then to viscoelastic materials by introducing internal variables. Extensive numerical results in these contexts are presented to assess the accuracy and stability properties of the proposed methods for general solid mechanics.
Finally, we describe a similar VMS-based finite element method for shock hydrodynamics, and conclude the presentation by coupling the two methods to perform challenging shock-solid interaction computations.
Biography: Xianyi Zeng obtained a BS in mathematics and applied mathematics from Peking University, and a PhD in computational and mathematical engineering from the Stanford University. Before joining the Civil and Environmental Engineering Department at Duke University as a postdoc, he worked on his dissertation in the Department of Aeronautics and Astronautics at Stanford University while pursuing the doctoral degree. Dr. Zeng has broad interests in computational mechanics and their applications, including computational gas dynamics, computational solid mechanics, fluid-structure interactions, and numerical modeling of inelastic materials, among others.
Host: Paul Ronney
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Valerie Childress
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Epstein ISE Department Seminar
Thu, Mar 05, 2015 @ 10:00 AM - 11:00 AM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Yongpei Guan, Associate Professor, Department of Industrial and Systems Engineering and Director, Computational and Stochastic Optimization Lab, University of Florida
Talk Title: Renewable Energy Integration and Data-Driven Risk-Averse Stochastic Optimization
Abstract:
Renewable energy has been increasingly penetrating into the power grid systems recently. Due to its intermittent nature, new challenges arise for power system operators to provide reliable unit commitment decisions to incorporate intermittent renewable generation, with the objective of ensuring system reliability while maintaining cost effectiveness.
In practice, the distribution of renewable energy output is unknown, and instead, only a set of historical data is available. This motives a theoretical study on data-driven risk-averse stochastic optimization. Starting from the given historical data set, we introduce a set of probability metrics to construct the confidence set for the unknown probability distribution through nonparametric statistical estimation. We accordingly formulate a risk-averse stochastic program (RASP) from the perspective of distributional robustness by hedging against the worst-case distribution within the confidence set and considering the corresponding expected total cost. In our study, for a specific metric, we can derive an equivalent reformulation for RASP, which explicitly reflects its linkage with a full spectrum of coherent risk measures under various risk-averseness levels. This reformulation result can be further extended to other interesting models in the stochastic programming literature including chance and stochastic dominance constraints. In addition, we develop a solution algorithm for the reformulation based on the sample average approximation method. We also perform convergence analysis to show that the risk-averseness of RASP vanishes as the data sample size grows to infinity, in the sense that the optimal objective value of RTSP converges to that of the risk-neutral one. Furthermore, we can show the âvalue of dataâ by analyzing the convergence rate of our solution approach for a family of metrics.
Finally, we apply the proposed solution framework to solve the reliability unit commitment problem with renewable energy integration, and the computational results show the effectiveness of our proposed approach.
This is joint work with Ruiwei Jiang and Chaoyue Zhao
Biography:
Yongpei Guan currently serves as an Associate Professor and the Director of the Computational and Stochastic Optimization Lab at the University of Florida. His research interests include nonparametric statistical estimation and stochastic optimization, discrete optimization, and stochastic impulse control with their applications in supply chain management and power system analysis with renewable energy integration. His works in these areas have led to NSF Career Award 2008 and Office of Naval Research Young Investigator Award 2010, and have been published in IEEE Transactions on Power Systems, Mathematical Programming, and Operations Research. His Ph.D. students have won the Nicholson Best Student Paper Award (first place) from INFORMS and Pritsker Doctoral Dissertation Awards (second and third places) from IIE. He is currently the associate editor for Journal of Global Optimization and Computational Optimization and Applications, as well as the newsletter editor for the INFORMS Computing Society. He was also nominated and served as the chair of the 2014 IIE Annual Conference ISERC Program, and invited and served as the 2013 Guest Editor-in-Chief for the Special Issue on âOptimization Methods and Algorithms Applied to Smart Gridâ for IEEE Transactions on Smart Grid. Yongpei Guan obtained his Ph.D. from Georgia Tech in 2005.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Information: SEMINAR-Guan.doc
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Lyman L. Handy Colloquia: Dehua Pei (Ohio State)
Thu, Mar 05, 2015 @ 12:45 PM - 02:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dehua Pei, Ohio State University Dept. of Chemistry
Talk Title: Inhibition of Protein-Protein Interactions with Macrocycles
Abstract: TBA
Host: Prof. Roberts
Location: James H. Zumberge Hall Of Science (ZHS) - 159
Audiences: Everyone Is Invited
Contact: Ryan Choi
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CS Colloquium: Prof. Ameet Talwalkar (UCLA) - Scalable and User-Friendly Machine Learning in Apache Spark
Thu, Mar 05, 2015 @ 04:00 PM - 05:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ameet Talwalkar, UCLA
Talk Title: Scalable and User-Friendly Machine Learning in Apache Spark
Series: CS Colloquium
Abstract: Modern datasets are rapidly growing in size and complexity, and this wealth of data holds the promise for many transformational applications. Machine learning is seemingly poised to deliver on this promise, having proposed and rigorously evaluated a wide range of data processing techniques over the past several decades. However, concerns over scalability and usability present major roadblocks to the wider adoption of these methods. In this talk I will describe the MLbase project, which aims to address these concerns by developing machine learning functionality on top of Apache Spark, a popular cluster computing engine designed for iterative computation. I will first describe MLlib, Sparkâs scalable machine learning library that grew out of the MLbase project. I will also discuss higher level components of MLbase, focusing on the problem of hyperparameter optimization as a means to simplify the task of machine learning pipeline construction.
Biography: Ameet Talwalkar is an assistant professor of Computer Science at UCLA and a technical advisor for Databricks. His research addresses scalability and ease-of-use issues in the field of statistical machine learning, with applications in computational genomics. He led the initial development of the MLlib project in Apache Spark and is a co-author of the graduate-level textbook 'Foundations of Machine Learning' (2012, MIT Press). Prior to UCLA, he was an NSF post-doctoral fellow in the AMPLab at UC Berkeley. He obtained a B.S. from Yale University and a Ph.D. from the Courant Institute at NYU.
Host: Fei Sha
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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W.V.T. Rusch Engineering Honors Colloquium
Fri, Mar 06, 2015 @ 01:00 PM - 02:00 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
Conferences, Lectures, & Seminars
Speaker: Eric Larson, Riviera Partners
Talk Title: 2014-2015 Hiring Marketplace
Host: W.V.T. Rusch Engineering Honors Program
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Jeffrey Teng
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Computer Engineering Seminar
Fri, Mar 06, 2015 @ 02:30 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Fernando Moraes, PUCRS (Pontifical Catholic University of Rio Grande do Sul), Porto Alegre, Brasil
Talk Title: Adaptability techniques for QoS and distributed management of MPSoCs
Abstract: Adaptability techniques - With the significant increase in the number of processing elements in NoC-Based MPSoCs, communication becomes, increasingly, a critical resource for performance gains and QoS guarantees. The main gap observed in the NoC-Based MPSoCs literature is the runtime adaptive techniques to meet QoS. In the absence of such techniques, the system user must statically define, for example, the scheduling policy, communication priorities, and the communication switching mode of applications. The goal of this research is to investigate the runtime adaptation of the NoC resources, according to the QoS requirements of each application running in the MPSoC. The present work adopts a NoC architecture with duplicated physical channels, adaptive routing, support to flow priorities and simultaneous packet and circuit switching. The monitoring and adaptation management is performed at the operating system level, ensuring QoS to the monitored applications. The QoS acts in the flow priority and the switching mode. Monitoring and QoS adaptation were implemented in software, resulting in flexibility to apply the techniques to other platforms or include other adaptive techniques, as task migration or DVFS. Applications with latency and throughput deadlines run concurrently with best-effort applications. Results with synthetic and real application reduced in average 60% the latency violations, ensuring smaller jitter and throughput. The execution time of applications is not penalized applying the proposed QoS adaptation methods.
Distributed Management - Scalability is an important issue in large MPSoCs. MPSoCs may execute several applications in parallel, with dynamic workload, and tight QoS constraints. Thus, the MPSoC management must be distributed to cope with such constraints. This talk presents a distributed resource management in NoC-Based MPSoC, using a clustering method, enabling the modification of the cluster size at runtime. This work addresses the following distributed techniques: task mapping, monitoring and task migration. Results show an important reduction in the total execution time of applications, reduced number of hops between tasks (smaller communication energy), and a reclustering method through monitoring and task migration.
Biography: Fernando Moraes received the Electrical Engineering and M.Sc. degrees from the Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil, in 1987 and 1990, respectively. In 1994 he received the Ph.D. degree from the Laboratoire d ÌInformatique, Robotique et Microélectronique de Montpellier (LIRMM), France. He is currently at PUCRS. From 1998 to 2000 he joined the LIRMM as an Invited Professor for 3 months each year. He has authored and co-authored 24 peer refereed journal articles in the field of VLSI design, comprising the development of networks on chip and telecommunication circuits. One of these articles, HERMES: an Infrastructure for Low Area Overhead Packet-switching Networks on Chip, is cited by more than 500 other papers. He has also authored and co-authored more than 180 conference papers on these topics. He has advised 23 MsC, advised 4 PhD and co-advised 3 PhD works. His primary research interests include Microelectronics, FPGAs, reconfigurable architectures, NoCs (networks on chip) and MPSoCs (multiprocessor system on chip). SBC, SBMICRO and IEEE Senior Member.
Host: Prof. Peter Beerel
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Integrated Systems Seminar
Fri, Mar 06, 2015 @ 03:00 PM - 04:30 PM
Conferences, Lectures, & Seminars
Speaker: Prof. Kwabena Boahen, Stanford University
Talk Title: TBD
Series: Integrated Systems Seminar
Host: Hosted by Prof. Hossein Hashemi, Prof. Mike Chen, and Prof. Mahta Moghaddam Organized and hosted by Run Chen
More Info: http://mhi.usc.edu/events/event-details/?event_id=915367
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Elise Herrera-Green
Event Link: http://mhi.usc.edu/events/event-details/?event_id=915367
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Mar 06, 2015 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Nasaran Bassam Zadeh and Ali Ghahramani, Astani CEE Ph.D. Candidates
Talk Title: TBA
Abstract: TBA
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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NL Seminar- Multi-site genetic analysis of the brain’s white matter: ENIGMA-DTI
Fri, Mar 06, 2015 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Neda Jahanshad, (USC/ISI)
Talk Title: Multi-site genetic analysis of the brainâs white matter: ENIGMA-DTI
Series: Natural Language Seminar
Abstract: The functioning regions of the brain are connected through a complex network of fibers, described by the brainâs white matter. Non-invasive imaging using MRI-based diffusion imaging can help capture important characteristics of the connections by describing the strength and directionality profile of water diffusion along white matter fibers. Variability in these connections have been noted in many neurological, degenerative, and psychiatric disorders where ultimately information transfer from on brain region to the other may be weakened or completely compromised. To discover genetic risk factors for altered connectivity and common genetic variants which put the brain at subtle risk for weakened connections, we find power in sample size and pool multiple datasets from around the world to determine common effects in all populations. However, there is no standard method for acquiring diffusion images and standardizing measures across datasets is an ongoing challenge. The Enhancing Neuro Imaging Genetics through Meta Analysis group on Diffusion Tensor Imaging has established a set of basic protocols to overcome a portion of these challenges, which I will describe, along with works-in-progress to tackle additional obstacles to reveal critical details of the brains network.
Biography: Neda Jahanshad is an assistant professor of Neurology at USC in the Imaging Genetics Center at ISI. She received her PhD in Biomedical Engineering at UCLA in 2012 where she worked on optimizing diffusion imaging protocols to map structural brain connections in large populations. She has since extended the work to explore methods of pooling such imaging data from across the world and determine genetic and environmental contributions to the connectivity of the brain and determine how these effects vary across the lifespan. She is coordinating one of the largest studies of the brain's white matter through the ENIGMA Consortium http://enigma.ini.usc.edu.
Host: Nima Pourdamghani and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 6th Flr Conf Rm # 689, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
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Seminar in Biomedical Engineering
Mon, Mar 09, 2015 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Albert Keung, PhD, NIH-NRSA Postdoctoral Fellow, MIT(IMES)-Boston University(BME), Boston, MA.
Talk Title: Synthetic Chromatin Biology
Abstract: The genomes of eukaryotic organisms including yeast, plants, and mammals are packaged into chromatin, a constellation of proteins and RNA physically layered on top of the polymeric genomic DNA. Chromatinâs rich structure and intimate association with the genome drives highly sophisticated gene expression programs and is relevant in diverse cellular processes from yeast metabolism to cancer to stem cell differentiation. Due to the hundreds of chromatin components and their functional diversity and complexity, there remain many questions and hypotheses surrounding the fundamental mechanisms of chromatin regulation. Furthermore, we are just beginning to reveal and quantitatively understand the potential gene regulatory behaviors chromatin confers to eukaryotic cells beyond gene activation and repression. In this talk, I will discuss how systems-scale synthetic biology approaches can help address fundamental questions about chromatin regulation, reveal complex gene regulation behaviors, and advance our ability to treat diverse disease states. I will describe a library of 223 synthetic proteins that site-specifically controls chromatin states in the yeast, S. cerevisiae. Recruitment of these synthetic chromatin regulators to custom genetic reporters reveals diverse regulatory behaviors including: 1) two-input logic; 2) long-range regulation; 3) asymmetric spatial regulation; and 4) gene expression memory. Through gene ontology clustering analysis, this synthetic system also provides insights into the protein functions driving these behaviors and can be used to address fundamental hypotheses in chromatin biology. Just as over 15 years ago synthetic biology built a conceptual and experimental framework around the manipulation of DNA sequences, new systems to control and harness chromatin will deepen our understanding of eukaryotic gene regulation and provide a powerful layer of cellular regulation for biomedical and biotechnological applications
Biography: Dr. Keung is a postdoctoral fellow at MIT and Boston University. His doctoral work focused on extracellular biophysical cues and their effects on stem cell differentiation and neurogenesis. Given the importance of chromatin in these processes, and its ubiquitous roles in eukaryotic gene regulation, Dr. Keung became broadly interested in engineering synthetic approaches to manipulate and harness chromatin and other epigenetic sources of cellular information, with the ultimate goals of advancing biological research, human health, and biotechnology.
Host: Stanley Yamashiro
Location: OHE 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Short Course: Six Sigma Green Belt for Process ImprovementTue, Mar 10, 2015
DEN@Viterbi, Executive Education
Conferences, Lectures, & Seminars
Abstract: This program, an introductory course in Six Sigma, will give you a thorough understanding of Six Sigma and its focus on eliminating defects through fundamental process knowledge. Topics covered in addition to DMAIIC and Six Sigma philosophy include basic statistics, statistical process control, process capability, financial implications and root cause analysis. This program is offered both in the classroom and online.
Register Now!
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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CS Colloquium: Elette Boyle (Technion Israel Institute of Technology) - Large-Scale Secure Computation
Tue, Mar 10, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Elette Boyle, Technion Israel Institute of Technology
Talk Title: Large-Scale Secure Computation
Series: CS Colloquium
Abstract: The ability to collect and process large data sets has unlocked exciting new technological and research discoveries. Unfortunately, in several important applications, it is not possible to leverage the full extent of collected data, when information consists of sensitive data sets held by individual agents who are either unable or unwilling to share the data itself (e.g., patients' medical information gathered by different medical studies).
A promising approach to enable data sharing within these scenarios is to make use of cryptographic tools such as secure multi-party computation (MPC). MPC protocols provide a means for mutually untrusting parties to jointly evaluate a global function f over their secret inputs, while guaranteeing that no information is revealed beyond the function output.
However, despite great progress in MPC techniques in the last three decades, the surrounding world of data aggregation and computation has leapt even more rapidly forward. For example, nearly all existing MPC protocols require each party to store information comparable to the {\em total} combined data, and evaluate the desired function via a {\em boolean circuit} representation. When the number of parties and size of data is large, or when the functions to be computed are "lightweight" (e.g. touching only small portions of the data), these limitations completely obliterate feasibility of MPC as a solution.
In this talk, I will introduce a new class of techniques yielding MPC protocols whose parameters scale to the modern regime of massive data.
Lecture will be available to stream HERE.
Biography: Elette is currently a postdoctoral researcher at the Technion Israel Institute of Technology. Prior to the Technion, Elette received her Ph.D. from MIT under the guidance of Shafi Goldwasser, held a short-term postdoc at Cornell University, and completed her B.S. at Caltech in mathematics. Elette's research is in cryptography, focusing on methods of secure computation and distributed algorithm design.
Host: Computer Science Department
More Info: https://bluejeans.com/175107895
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/175107895
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EE-EP Seminar
Tue, Mar 10, 2015 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Li Jun Jiang, Dept. of Electrical and Electronic Engineering, the University of Hong Kong
Talk Title: COMPUTATIONAL ELECTROMAGNETICS AND ITS APPLICATIONS FROM DC TO OPTICS
Abstract: Due to the pervasive use of computing powers, computational electromagnetics (CEM) has become an indispensable technology for maintaining Mooreâs law in semiconductor industries, engineering new electromagnetic and optical materials, characterizing the next generation nano devices, and accelerating future communication systems. Facing surging scientific and engineering demands, the complexity of physics in todayâs CEM researches is unprecedented. Because of close connections between electromagnetics and optics, CEM generates essential methodologies and insights to new advances from static circuits, microwave systems, to THz and optical devices.
There are several primary challenges that CEM is facing: complex environments, extreme frequencies, and multidisciplines. The first two are heavily referenced and employed by the last one for advances in optoelectronics and nano scale devices. By developing physical models and numerical engines, I have been addressing above issues with novel solutions. New integral equation methods in the frequency domain and discontinuous Galerkinâs methods in the time domain have been proposed by us to characterize problems that are homogeneous or inhomogeneous, linear or nonlinear, isotropic or anisotropic, deterministic or stochastic, etc. The numerical fast multipole algorithms and other divide and conquer strategies rooted from physical principles are employed to organize numerical solutions. At the low frequency, the decoupling of electronic and magnetic fields is employed to establish a stable system. For the broadband request, both evanescent and propagating properties are integrated to support a smooth transition from the circuit physics to wave physics. By further pushing up the frequency, novel computational solutions for optoelectronic devices and graphene have been successfully developed to characterize the electromagnetic field with them. By demonstrating computational solutions ranging from DC, microwave, THz, to optical applications, the talk will conclude with future research discussions.
Biography: Lijun Jiang (Sâ01-Mâ04-SMâ13) received his Bachelor degree from the Beijing University of Aeronautics and Astronautics, Master degree from Tsinghua University, and Ph.D from the University of Illinois at Urbana-Champaign in summer 2004. He worked as the application engineering at Hewlett-Packard (HP) in 1996-1999. From 2004 to 2009, he was postdoc/research staff member/senior engineer at IBM T.J. Watson Research Center, NY. Since the end of 2009, he has been an Associate Professor with the Department of Electrical and Electronic Engineering at the University of Hong Kong, where he received his tenure in Summer 2014. Since Sept. 2014, he has been a visiting scholar at the University of California, Los Angeles (UCLA) for his Sabbatical leave.
He has received many recognitions including the HP STAR Award in 1998 at HP, the Y.T. Lo Outstanding Research Award in 2004 at UIUC, the IBM Research Technical Achievement Award in 2008 at IBM Research, the Best Student Paper Award of 2014 ACES in Florida, and the Best Paper Award of 2014 IEEE EPEP in Oregon. He is the Associate Editor of IEEE Transactions on Antennas and Propagation, the Associate Editor of Progress in Electromagnetics Research, the Associate Guest Editor of the Proceedings of IEEE Special Issue in 2011~2012, IEEE Senior Member, and the member of many international academic associations. He was the Semiconductor Research Cooperation (SRC) Industrial Liaison for several academic projects. He was the TPC member, session organizer, or session chair of many international conferences. He was the co-organizer of HKU Computational Science and Engineering Workshops in 2010-2012, the TPC co-chair of the 7th International Conference on Nanophotonics (ICNP), the co-chair of International Workshop on Pulsed Electromagnetic Field at the Delft, the Netherlands, 2013, and the TPC co-chair of 14th International FEM Workshop. He serves as the reviewer for almost all major electromagnetics and microwave related journals.
His research interests focus on electromagnetics and optics, computational electromagnetics, IC signal/power integrity, IC EMC/EMI, microwave material engineering, etc.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Dynamics and control of distributed systems
Tue, Mar 10, 2015 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mihailo Jovanovic, University of Minnesota
Talk Title: Dynamics and control of distributed systems
Abstract: In the first part of the talk, we examine fundamental limitations arising from the use of local feedback in networks subject to stochastic disturbances. For vehicular formation control problems in topology of regular lattices we show that it is impossible to have coherent large formations, that behave like rigid lattices, in one and two spatial dimensions. Yet we prove that this is achievable in 3D. The observed phenomenon is a consequence of the fact that, in 1D and 2D, local feedback laws are ineffective in guarding against disturbances with large spatial wavelength. We provide connections with several other problems including distributed averaging algorithms, global mean first passage time of random walks, effective resistance in electrical networks, and statistical mechanics of harmonic solids. We close the first part of the talk by demonstrating how tools and ideas from control theory, optimization, and compressive sensing can be combined to identify network topologies that strike desired tradeoff between the performance and sparsity.
In the second part of the talk, techniques from control theory are used to study the early stages of transition to turbulence in wall-bounded shear flows. We demonstrate high sensitivity of the flow equations to modeling imperfections and show that control theory can be used not only to design flow control algorithms but also to provide valuable insights into the transition mechanisms.
Biography: Mihailo Jovanovic (www.umn.edu/~mihailo) is an Associate Professor of Electrical and Computer Engineering at the University of Minnesota. He has held visiting positions with Stanford University and the Institute for Mathematics and its Applications. His current research focuses on fundamental limitations in the design of large dynamic networks, sparsity-promoting optimal control, and dynamics and control of fluid flows. He is a senior member of IEEE and currently serves as an Associate Editor of the SIAM Journal on Control and Optimization. He served as an Associate Editor of the IEEE Control Systems Society Conference Editorial Board from July 2006 until December 2010. Prof. Jovanovic received a CAREER Award from the National Science Foundation in 2007, an Early Career Award from the University of Minnesota Initiative for Renewable Energy and the Environment in 2010, a Resident Fellowship within the Institute on the Environment at the University of Minnesota in 2012, the George S. Axelby Outstanding Paper Award from the IEEE Control Systems Society in 2013, the University of Minnesota Informatics Institute Transdisciplinary Research Fellowship in 2014, and the Distinguished Alumni Award from UC Santa Barbara in 2014.
Host: Petros Ioannou
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Shane Goodoff
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Dynamics and control of distributed systems
Tue, Mar 10, 2015 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mihailo Jovanovic, University of Minnesota
Talk Title: Dynamics and control of distributed systems
Abstract: In the first part of the talk, we examine fundamental limitations arising from the use of local feedback in networks subject to stochastic disturbances. For vehicular formation control problems in topology of regular lattices we show that it is impossible to have coherent large formations, that behave like rigid lattices, in one and two spatial dimensions. Yet we prove that this is achievable in 3D. The observed phenomenon is a consequence of the fact that, in 1D and 2D, local feedback laws are ineffective in guarding against disturbances with large spatial wavelength. We provide connections with several other problems including distributed averaging algorithms, global mean first passage time of random walks, effective resistance in electrical networks, and statistical mechanics of harmonic solids. We close the first part of the talk by demonstrating how tools and ideas from control theory, optimization, and compressive sensing can be combined to identify network topologies that strike desired tradeoff between the performance and sparsity.
In the second part of the talk, techniques from control theory are used to study the early stages of transition to turbulence in wall-bounded shear flows. We demonstrate high sensitivity of the flow equations to modeling imperfections and show that control theory can be used not only to design flow control algorithms but also to provide valuable insights into the transition mechanisms.
Biography: Mihailo Jovanovic (www.umn.edu/~mihailo) is an Associate Professor of Electrical and Computer Engineering at the University of Minnesota. He has held visiting positions with Stanford University and the Institute for Mathematics and its Applications. His current research focuses on fundamental limitations in the design of large dynamic networks, sparsity-promoting optimal control, and dynamics and control of fluid flows. He is a senior member of IEEE and currently serves as an Associate Editor of the SIAM Journal on Control and Optimization. He served as an Associate Editor of the IEEE Control Systems Society Conference Editorial Board from July 2006 until December 2010. Prof. Jovanovic received a CAREER Award from the National Science Foundation in 2007, an Early Career Award from the University of Minnesota Initiative for Renewable Energy and the Environment in 2010, a Resident Fellowship within the Institute on the Environment at the University of Minnesota in 2012, the George S. Axelby Outstanding Paper Award from the IEEE Control Systems Society in 2013, the University of Minnesota Informatics Institute Transdisciplinary Research Fellowship in 2014, and the Distinguished Alumni Award from UC Santa Barbara in 2014.
Host: Petros Ioannou
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Shane Goodoff
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Epstein Institute / ISE 651 Seminar Series
Tue, Mar 10, 2015 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ann Bisantz, Professor and Chair, Industrial and Systems Engineering, The University at Buffalo, State University of New York
Talk Title: Meta-Information Visualization: A Human Factors Approach
Abstract: In many domains, users are confronted with large volumes of information from a variety of sources. In addition to understanding the content of the information, they need to understand and reason about potential qualifiers of the information. These qualifiers, or meta-information, include characteristics such as the uncertainty associated with the data, the age of the data, and the source of the data. There is a long history of research in scientific visualization and geospatial information systems which has considered visual techniques for representing complex information, in both spatial and non-spatial frames of reference. Our own research has considered how visual techniques such as pixilation, transparency, saturation, and texture can be used to represent a variety of meta-information categories. This talk will survey results from a number of empirical studies which have examined how people interpret meta-information visualization regarding geospatial regions and objects, how different visualizations impact decision-making and task performance, and how these measure are affected by type of meta-information, task demands, and visual context.
Biography: Dr. Ann Bisantz performs research in areas of cognitive engineering, human-computer interface design, complex work system analysis. She is currently Professor and Chair of Industrial and Systems Engineering at the University at Buffalo, State University of New York. Dr. Bisantz received a PhD in Industrial and Systems Engineering from the Georgia Institute of Technology and an MS and BS in Industrial Engineering from the University at Buffalo. Her research includes developing novel information displays for complex systems, advancing methods in cognitive engineering, and modeling human decision-making; she has worked extensively in domains of health care and defense. She has an active research program regarding visualization of information qualifiers such as uncertainty, trust in information, and decision making which has been funded through a number of defense organizations as well as through a CAREER award from the National Science Foundation. She has collaborated with the University at Buffaloâs Center for Multi-Source Information Fusion and is currently a co-investigator on a MURI program funded by the Army Research Office regarding Hard-Soft Information Fusion. She is also collaborating with health informatics researchers and clinicians on research regarding health IT usability, workflow impacts and human factors of electronic health records and has conducted patient safety studies including risk analysis studies; and simulation and field studies of emergency department patient tracking systems. She co-edited the book âApplications of Cognitive Work Analysisâ (2008, CRC Press). She is a Fellow of the Human Factors and Ergonomics Society and Associate Editor of both the Journal of Cognitive Engineering and Decision Making, and IIE Transactions on Occupational Ergonomics. Dr. Bisantz was appointed ISE department chair in 2012.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Information: Seminar-Bisantz.docx
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Short Course: Six Sigma Green Belt for Process Improvement
Wed, Mar 11, 2015
DEN@Viterbi, Executive Education
Conferences, Lectures, & Seminars
Abstract: This program, an introductory course in Six Sigma, will give you a thorough understanding of Six Sigma and its focus on eliminating defects through fundamental process knowledge. Topics covered in addition to DMAIIC and Six Sigma philosophy include basic statistics, statistical process control, process capability, financial implications and root cause analysis. This program is offered both in the classroom and online.
Register Now!
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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Beyond Prosthetics: Turning Science Fiction into Science, and Science into Technology
Wed, Mar 11, 2015 @ 11:00 AM - 12:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dr. Phillip Alvelda, Program Manager, Biological Technologies Office; DARPA
Talk Title: Beyond Prosthetics: Turning Science Fiction into Science, and Science into Technology
Abstract: Dr. Alvelda's vision is to take the latest neural engineering science and technology out of the laboratory and seed the creation of new mind-enabled industries. The purpose of this seminar is to have discussions to explore highly-scalable direct neural interface technologies in order to design and develop complete systems that can go beyond simply restoring lost function. This research will require collaboration across multiple disciplines, including optics/photonics, medical materials and packaging, and neuroscience. This seminar is intended to be an opportunity for discussion with 40 minutes allocated for Q&A.
Biography: A scientist, engineer, serial entrepreneur, and educator, highlights of Dr. Alveldaâs career include developing sensors that have flown throughout the solar system, establishing an entirely new infrastructure in telecommunications and media at companies that he founded, including the DARPA-funded MicroDisplay, and MobiTV, and founding the non-profit Westminster Institute for K-12 Science Education reform (wiseteachers.org). Dr. Alvelda holds over 50 technical publications and numerous patents, a Technical Emmy award from the Academy of Motion Pictures, a Bachelorâs degree in Physics from Cornell University, and Masters and PhD degrees in Computer Science and Electrical Engineering from the Massachusetts Institute of Technology. He is also a World Economic Forum Technology Pioneer.
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Everyone Is Invited
Contact: Ryan Choi
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Spring 2015 Environmental Engineering Seminar Series
Wed, Mar 11, 2015 @ 03:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jeanne VanBriesen, Carnegie Mellon University
Talk Title: Effects of Fossil Fuel Extraction and Utilization Wastewaters on Drinking Water Treatment Processes
Host: Katie Russo
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Kaela Berry
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Aerospace and Mechanical Engineering Seminar Series
Wed, Mar 11, 2015 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Mac Schwager, Assistant Professor in Mechanical Engineering and Systems Engineering at Boston University, Boston, MA
Talk Title: Multi-Robot Systems for Monitoring and Controlling Large Scale Environments
Series: Aerospace and Mechanical Engineering Seminar Series
Abstract: Groups of aerial, ground, and sea robots working collaboratively have the potential to transform the way we sense and interact with our environment at large scales. They can serve as eyes-in-the-sky for environmental scientists, farmers, and law enforcement agencies, providing critical, real-time information about dynamic environments and cityscapes. They can even help us to control large-scale environmental processes, autonomously cleaning up oil spills, tending to the needs of crop lands, and fighting forest fires, while humans stay at a safe distance. This talk will present an overview of research toward the realization of this vision, giving special attention to recent work on distributed optimization-based control algorithms for groups of aerial robots to monitor large-scale environments. I will describe a general optimization-based control design methodology for synthesizing practical, distributed robot controllers with provable stability and convergence properties. I will also describe low-level control techniques based on differential flatness to coordinate the motion of teams of quadrotors in an agile and computationally efficient manner. Experimental studies with groups of quadrotor robots flying both outdoors and indoors using these controllers will also be discussed.
Biography: Mac Schwager is an assistant professor in the Department of Mechanical Engineering and the Division of Systems Engineering at Boston University. He obtained his BS degree in 2000 from Stanford University, his MS degree from MIT in 2005, and his PhD degree from MIT in 2009. He was a postdoctoral researcher working jointly in the GRASP lab at the University of Pennsylvania and CSAIL at MIT from 2010 to 2012. His research interests are in distributed algorithms for control, perception, and learning in groups of robots and animals. He received the NSF CAREER award in 2014.
Host: Paul Ronney
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Valerie Childress
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EE Pioneer Series – Robert W. Hellwarth
Wed, Mar 11, 2015 @ 04:00 PM - 06:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Robert W. Hellwarth, University Professor, Professor of Electrical Engineering and Physics and Astronomy
Talk Title: TBD
Series: Pioneer Series
Biography: Professor Robert W. Hellwarth, University Professor, Professor of Electrical Engineering and Physics and Astronomy, and holder of the George T. Pfleger Chair in Electrical Engineering, joined the University of Southern California in 1970. Over the past 45 years, Professor Hellwarth has made numerous outstanding research contributions in the areas of quantum electronics; nonlinear optics; design and employment of lasers to aid a variety of practical and scientific efforts, from adaptive optics for astronomy to electro-optic modulators for communications. Professor Hellwarth has received several honors including the Charles Hard Townes Award of the Optical Society of America, the Quantum Electronics Award of the IEEE, and he is member of both the National Academy of Sciences and the American Academy of Arts and Sciences.
Host: Ming Hsieh Institute
More Info: http://mhi.usc.edu/about/news/2015/02/18/ee-pioneer-series-robert-w-hellwarth/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Elise Herrera-Green
Event Link: http://mhi.usc.edu/about/news/2015/02/18/ee-pioneer-series-robert-w-hellwarth/
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Astani Civil and Environmental Engineering Seminar
Wed, Mar 11, 2015 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jeanne VanBriesen, Carnegie Mellon University
Talk Title: Effects of fossil fuel extraction and utilization wastewaters on drinking water treatment processes
Abstract:
Changes in human activities associated with fossil fuel extraction and utilization can alter source waters in ways that affect treatment choices, costs, and the quality of the finished water distributed for human consumption. Produced waters from oil and gas extraction, especially those associated with shale formations, are often high in salts and bromide. Discharge of these wastewaters, even after partial treatment, can increase surface water concentrations of dissolved solids and bromide. Similarly, coal-fired power plants can produce wastewater with high dissolved solids, where the bromide concentration depends on the source coal, the addition of bromide for mercury control, and the use of pollution control devices such as flue-gas desulfurization units. These new or increasing sources of bromide have the potential to affect drinking water treatment plants. Several areas of the country not traditionally associated with high source water bromide levels (including the Ohio River Basin) have been reporting increasing bromination of disinfection by-products (DBPs) in treated drinking water. These changes may require changes to treatment at the drinking water plant or new methods for DBP control in the distribution system. This represents a significant challenge for drinking water infrastructure in the United States. A recently completed three year field study, and an analysis of state and industry reports for produced water quantity and quality, along with power plant discharge data, enables an assessment of the effect of fossil fuel extraction and utilization activities on source water quality and finished water disinfection by-products in the Monongahela River in Southwestern Pennsylvania.
Biography:
Dr. Jeanne M. VanBriesen is the Duquesne Light Company Professor of Civil and Environmental Engineering at Carnegie Mellon University. Dr. VanBriesen holds a B.S. in Education and a M.S. and Ph.D. in Civil Engineering from Northwestern University. She is a licensed professional engineer in the state of Delaware. Her research focuses on biotransformation of recalcitrant organics, detection of biological agents in drinking water and natural water systems, and speciation-driven biogeochemistry of chelating agents and disinfection by-products. Dr. VanBriesen has published fifty scientific papers and given more than 100 professional presentations. Her research has been funded by the National Science Foundation, the Department of Defense, the Colcom Foundation, the Heinz Endowments, the Packard Foundation, and the Pennsylvania Infrastructure Technology Alliance. Dr. VanBriesen has served on the boards of the Association for Environmental Engineering and Science Professors and the Ohio River Basin Consortia for Research and Education. She is currently serving on the U.S.EPA Science Advisory Board.
Host: Dr. Amy Childress
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Short Course: Six Sigma Green Belt for Process Improvement
Thu, Mar 12, 2015
DEN@Viterbi, Executive Education
Conferences, Lectures, & Seminars
Abstract: This program, an introductory course in Six Sigma, will give you a thorough understanding of Six Sigma and its focus on eliminating defects through fundamental process knowledge. Topics covered in addition to DMAIIC and Six Sigma philosophy include basic statistics, statistical process control, process capability, financial implications and root cause analysis. This program is offered both in the classroom and online.
Register Now!
Audiences: Registered Attendees
Contact: Viterbi Professional Programs
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CS Colloquium: Elias Bareinboim (UCLA) - Generalizability in Causal Inference
Thu, Mar 12, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Elias Bareinboim, UCLA
Talk Title: Generalizability in Causal Inference
Series: CS Colloquium
Abstract: Empirical scientists seek not just surface descriptions of the observed data, but deeper explanations of why things happened the way they did, and how the world would be like had things happened differently. With the unprecedented accumulation of data (or, âbig dataâ), researchers are becoming increasingly aware of the fact that traditional statistical techniques, including those based on artificial intelligence and machine learning, must be enriched with two additional ingredients in order to construct such explanations:
1. the ability to integrate data from multiple, heterogeneous sources, and
2. the ability to distinguish causal from associational relationships.
In this talk, I will present a theory of causal generalization that provides a principled way for fusing pieces of empirical evidence coming from multiple, heterogeneous sources. I will first introduce a formal language capable of encoding the assumptions necessary to express each problem instance. I will then present conditions and algorithms for deciding whether a given problem instance admits a consistent estimate for the target effects and, if feasible, fuse information from various sources to synthesize such an estimate. These results subsume the analyses conducted in various fields in the empirical sciences, including âexternal validity,â âmeta-analysis,â âheterogeneity,â âquasi-experiments,â âtransportability,â and âsampling selection bias.â I will conclude by presenting new challenges and opportunities opened by this research.
The lecture will be available to stream Here.
Biography: Elias Bareinboim is a postdoctoral scholar (and was a Ph.D. student) in the Computer Science Department at the University of California, Los Angeles, working with Judea Pearl. His interests are in causal and counterfactual inferences and their applications. He is also broadly interested in artificial intelligence, machine learning, robotics, and philosophy of science. His doctoral thesis provides the first general framework for solving the generalizability problems in causal inference -- which has applications across all the empirical sciences. Bareinboim's recognitions include the Dan David Prize Scholarship, the Yahoo! Key Scientific Challenges Award, the Outstanding Paper Award at the 2014 Annual Conference of the American Association for Artificial Intelligence (AAAI), and the Edward K. Rice Outstanding Graduate Student.
Host: Computer Science Department
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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EE-EP Seminar
Thu, Mar 12, 2015 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Rajib Rahman, Purdue University
Talk Title: Atomistic modeling of solid-state devices: from qubits to transistors
Abstract: Due to aggressive scaling, todayâs transistors have reached sizes of tens of nanometers and are fast approaching the ultimate limits of scaling, as predicted by Mooreâs Law. At the nanoscale, the atomic granularity of the devices and the associated quantum mechanical effects strongly influence device operation and need to be considered in theoretical models. To ensure continued progress in computing in the post Mooreâs Law era, novel device concepts need to be developed utilizing quantum phenomena at the nanoscale. I will present an atomistic modeling technique for solid-state devices that combine material and device level description of electronic structure and transport from a full quantum mechanical treatment. This framework helps to model a variety of systems ranging from solid-state qubits to field-effect-transistors, and can help in designing the next generation of electronic devices.
In particular, I will show several applications of this method to model silicon qubits hosted in quantum dots and donors. 1) The method captures the precise electric field control of electronic and nuclear spins in donor qubits through the hyperfine and spin-orbit interactions [1], and helps in the first experimental realization of the Kane A-gate [2]. 2) Spin-lattice relaxation times are computed from an atomistic electron-phonon Hamiltonian to interpret experimental measurements, and design guidelines are presented to enhance the relaxation times by an order of magnitude [3]. 3) Electron-electron interaction is captured from a full configuration interaction technique in the tight-binding basis, and is used to obtain two-qubit exchange energy as a function of detuning electric field and qubit separation. Design considerations are presented to improve the electric-field tunability of exchange by several orders of magnitude in donor qubits. The computed single and multi-electron wavefunctions are also compared with tunneling probability measurements in scanning tunneling microscopy experiments to identify signatures of conduction band valley quantum interference in silicon [4].
I will also show atomistic quantum transport simulations of tunnel field-effect transistors (FET) in the emerging class of two-dimensional transition metal dichalcogenides. The simulations elucidate the material choice and design principles needed to achieve a steep sub-threshold slope transistor with large on-currents and high on/off ratio, which may help to scale down the power supply voltage and thus reduce the power consumption [5].
References:
[1] R. Rahman et. al., Phys. Rev. Lett. 99, 036403 (2007).
[2] B. E. Kane, Nature 393, 133 (1998).
[3] Y. Hsueh et. al., Phys. Rev. Lett. 113, 246406 (2014).
[4] J. Salfi et. al., Nature Materials 13, 605 (2014).
[5] H. Ilatikhameneh et. al., arXiv: 1502.01760 (2015).
Biography: Rajib Rahman obtained his PhD degree in Electrical and Computer Engineering from Purdue University in 2009 in the area of computational nanoelectronics. Subsequently, Rajib spent three years in Sandia National Laboratories, New Mexico, as a postdoctoral fellow in the Silicon Quantum Information Science and Technology group. Both in his PhD and postdoc, Rajib developed large-scale computational techniques in the NEMO3D tool to investigate the properties of quantum bits in silicon based on quantum dots and impurities. In 2012, Rajib joined Purdue University as a Research Assistant Professor in the Network for Computational Nanotechnology (NCN). Rajib currently leads the device modeling effort of the Australian Centre for Quantum Computer and Communication Technology (CQC2T), and investigates silicon qubits and their interaction with a solid-state environment. At Purdue, Rajib also works on novel low energy field-effect transistors in emerging materials such as 2D transition metal dichalcogenides, graphene, and polarization engineered Nitride devices.
Host: EE-Electrophysics
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Control of Spreading Processes on Networks
Thu, Mar 12, 2015 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Cameron Nowzari, University of Pennsylvania
Talk Title: Control of Spreading Processes on Networks
Abstract: The prevalence of social networks, robotic networks, power systems, and the Internet of Things today necessitates the development of a new interdisciplinary science catered to studying these complex networks. Some of the fundamental problems that can benefit from such a science include consensus, distributed estimation and control, and network and topology design. In this talk, we focus on the analysis and control of various spreading processes. The spreading of a disease through a population, the adoption of an idea or rumor through a social network, the consumption of a product in a marketplace, or the risk of receiving a computer virus through the world wide web are all prevalent examples of spreading processes we encounter every day. With the vast amount of application areas, it is no surprise that we have seen a recent surge of interest in these problems and the area of Network Science in general.
One of the most popular models of spreading processes is the Susceptible-Infected-Susceptible (SIS) model. Although a plethora of variations to the SIS model have been studied and analyzed by mathematicians, physicists, computer scientists, and biologists for over a century, there is still a severe lack in understanding how to effectively control these systems. With the freshly renewed interest in this topic, control engineers have only recently entered the scene and have a lot to offer. Focusing on the application of a disease spreading through a population, such as ebola or measles, we will look at how to best minimize the chance of it becoming an epidemic. We formulate the problem for a much more general model than the SIS model and propose an optimization framework that allows us to solve it efficiently.
Biography: : Cameron Nowzari received his B.S. in Mechanical Engineering from the University of California, Santa Barbara in June 2009. He received his M.S. and Ph.D. in Engineering Sciences from the University of California, San Diego in December 2010 and September 2013, respectively. He is currently working as a Postdoctoral Research Associate at the University of Pennsylvania. His research interests include dynamical systems and control, sensor networks, distributed coordination algorithms, optimization, robotics, event- and self-triggered control, Markov processes, and spreading processes. He was a finalist for the Best Student Paper Award at the 2011 American Control Conference and received the 2012 O. Hugo Schuck Best Paper Award in the Theory category for his work on distributed self-triggered coordination of mobile robotic networks.
Host: Urbashi Mitra, ubli@usc.edu, EEB 536, x04667
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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W.V.T. Rusch Engineering Honors Colloquium
Fri, Mar 13, 2015 @ 01:00 PM - 01:50 PM
Viterbi School of Engineering Student Affairs
Conferences, Lectures, & Seminars
Speaker: Alyse Killeen, Early-Stage Venture Capitalist,
Talk Title: Innovation with Distributed Network Technologies and the (related) VC Funding Environment
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Julie Phaneuf
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Communications, Networks & Systems (CommNetS) Seminar
Fri, Mar 13, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Nuno Martins, University of Maryland
Talk Title: Remote and Distributed Estimation over Shared Networks: New Results and Open Problems
Series: CommNetS
Abstract: This talk will focus on the design of distributed estimation systems that are formed by multiple non-collocated components. A shared network is used to disseminate information among the components.
I will discuss two recent results: Assuming that the network is characterized by an incomplete directed communication graph, the first result characterizes the existence of omniscience-achieving schemes for which all components that observe only a portion of the output of an underlying plant can estimate the entire state with error that vanishes asymptotically. Our approach hinges on key concepts from decentralized control that are systematic and constructive. The second result characterizes the structure of certain optimal policies for the case in which the number of components exceeds the maximal number of simultaneous transmissions that the network can accept. In order to obtain a tractable framework for which design principles can be characterized analytically, I will consider the case in which there are two estimators that rely on information sent to them by two sensors that access dissimilar measurements. I will show the optimality of certain threshold-based policies, establish a connection with a problem of optimal quantization for which the distortion is non-uniform across representation symbols, present numerical approaches, discuss interpretations of the results and list related open issues.
Biography: Nuno Martins is Associate Professor of Electrical and Computer Engineering at the University of Maryland, College Park, where he also holds a joint appointment with the Institute for Systems Research. From 2012 until 2014 he was the Director of the Maryland Robotics Center.
Martins holds a Ph.D. degree in Electrical Engineering and Computer Science with a minor in Mathematics from Massachusetts Institute of Technology (MIT), Cambridge. His research interests are in distributed control and estimation, team decision, optimization, networked control and communications.
He received a National Science Foundation CAREER award in 2007, the 2006 American Automatic Control Council O. Hugo Schuck Award, the 2010 Outstanding Institute for Systems Research Faculty award and the 2008 IEEE CSS Axelby Award for the best paper in the IEEE Transactions on Automatic Control.
He has served as a member of the editorial board of Systems and Control Letters (Elsevier), Automatica and of the IEEE Control Systems Society Conference Editorial Board. He was a program vice-chair for the IEEE Conference on Decision and Control in 2013 and 2014.
Host: Prof. Ashutosh Nayyar and the Ming Hsieh Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Seminar in Biomedical Engineering
Mon, Mar 16, 2015 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Talk Title: NO CLASS (SPRING BREAK)
Host: Stanley Yamashiro
Location: OHE 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Creating Love through Science
Fri, Mar 20, 2015 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jon Morra, Ph.D., Principal Machine Learning Engineer at eHarmony
Talk Title: Creating Love through Science
Series: AISeminar
Abstract: eHarmony has been creating successful matches for over 15 years. Over that time, our processes have grown in complexity from handmade linear functions to very complex multi-stage pipelines involving some of the latest techniques in data processing, data mining, and machine learning. In this talk I will go over our current data pipeline and highlight recent changes, including the addition of image processing and contextual bandit learning to help improve users' experience on our site. I will also touch upon the future of both our machine learning pipeline and algorithm selection at eHarmony.
Biography: Jon Morra, Ph.D., is a Principal Machine Learning Engineer at eHarmony. His work focuses on eHarmony's machine learning pipeline, including feature extraction, model creation, and data analysis in addition to contributing to the eHarmony engineering infrastructure. Before eHarmony, he co-founded a medical imaging company focused on image segmentation for therapy planning in radiation oncology and developed a novel image segmentation algorithm that was able to find various regions of interest in multi modality imaging environments. Jon has also spent time writing PACS software and developing Ruby on Rails techniques for radiation safety. He received his B.S. in Biomedical Engineering from Johns Hopkins University and his M.S. and Ph.D. in Biomedical Engineering from UCLA.
Host: Ashish Vaswani
Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=89ba5d5ed8c640d4aff1b850b308173c1dLocation: Information Science Institute (ISI) - 1135
WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=89ba5d5ed8c640d4aff1b850b308173c1d
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
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NL Seminar-Multitask Word Alignment with Random-Walk Regularizers
Fri, Mar 20, 2015 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Tomer Levinboim, Notre Dame University
Talk Title: Multitask Word Alignment with Random-Walk Regularizers
Series: Natural Language Seminar
Abstract: Suppose we translate a word from English to French and back. Should we get the original English word? That is, is translation invertible? Alternatively, suppose we translate an English word e to Spanish and then from Spanish to French, obtaining a word f. Should e-f be a valid entry in an English-French dictionary? That is, is translation transitive? Intuitively, if translation is done carefully, we expect to answer both these questions with "Yes, with high probability". In this talk, I will discuss how to formulate our intuition about invertibility/transitivity with random-walks, using translation probability distributions. I will then present two random-walk based regularization techniques that we recently used in a multitask word alignment setting: (1) Model Invertibility Regularization (MIR) - a concave regularizer for bi-directional models which can be applied even without parallel data. (2) Triangulation based Dirichlet prior - a method that capitalizes on parallel data with a pivot language, to construct and learn better translation priors. This talk is based on joint work with Prof. David Chiang (ND) and Dr. Ashish Vaswani (ISI).
Biography: Tomer Levinboim is a PhD student at the University of Notre Dame, working with Prof. David Chiang on developing machine learning techniques for improving machine translation and NLP of low resource languages. He is generously hosted by Kevin Knight at USC/ISI.
Host: Nima Pourdamghani and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 6th Flr Conf Rm # 689, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
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Information, Inference, and Privacy
Mon, Mar 23, 2015 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Flavio du Pin Calmon, MIT
Talk Title: Information, Inference, and Privacy
Abstract: Widespread collection of data has led to new and challenging privacy and security risks. There is a need to engineer mechanisms that allow users to selectively disclose their data to a third party in order to achieve a utility goal (e.g. receive high quality product recommendations), while restricting the release of private information (e.g. not revealing a given medical condition). In this talk, we use tools from information theory, statistics and estimation theory to characterize the fundamental limits of estimation when only partial statistics of the data are known. We then apply the insight gained by characterizing these limits to quantify the fundamental privacy-utility tradeoff and to design privacy-assuring mechanisms.
In addition, we introduce security metrics and associated results based on the spectrum of the conditional expectation operator, called the principal inertia components. The principal inertia components allow a fine-grained decomposition of the dependence between a hidden and an observed variable which, in turn, is useful for deriving fundamental bounds for estimation problems, and for measuring information leakage in secure communication models. Finally, we illustrate how our results can be used as a design driver for applications in security, noisy computation and distributed systems.
Biography: Flavio du Pin Calmon is a PhD candidate in Electrical Engineering and Computer Science (with a minor in Mathematics) at MIT, and a member of the Network Coding and Reliable Communications Group at the Research Laboratory of Electronics (RLE). His research interests include information theory, statistics, estimation theory, security and privacy. In addition to his work at MIT, Flavio has ongoing collaborations with the MIT Lincoln Laboratory, Technicolor SA and NetApp. Before coming to MIT, he received an M.Sc. in Electrical Engineering from the Universidade Estadual de Campinas, Brazil, and a B.Sc. in Communications Engineering from the Universidade de Brasilia, Brazil.
Host: Andreas Molisch
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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Seminar in Biomedical Engineering
Mon, Mar 23, 2015 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Xuefeng Wang, PhD, Postdoctoral Research Associate, Institute of Genomic BIology & Department of Physics University of Illinois at Urbana-Champaign
Talk Title: CANCELLED
Abstract: tba
Host: Stanley Yamashiro
Location: OHE 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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RASC Seminar Event: Prof. Carrick Detweiler (University of Nebraska-Lincoln) - Bringing Aerial Robots Closer to the Water: Sensing, Sampling, and Safety
Mon, Mar 23, 2015 @ 12:30 PM - 02:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Carrick Detweiler, University of Nebraska-Lincoln
Talk Title: Bringing Aerial Robots Closer to the Water: Sensing, Sampling, and Safety
Series: RASC Seminar Series
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly being used for everything from crop surveying to pipeline monitoring. They are significantly cheaper than the traditional manned airplane or helicopter approaches to obtaining aerial imagery and sensor data. The next generation of UAVs, however, will do more than simply observe. In this talk, I will discuss the challenges of using aerial robots very close to the water to obtain aerial water samples and sensor data from remote waters locations without needing to bring a boat to each location. When flying close to water, there is little time to react to errors and among obstacles. I will discuss automated software analysis techniques we are developing to detect and correct system errors to reduce risk and increase safety. I will focus on our recent work on the UAV-based water sampler system, but also discuss other applications we are pursuing, including using UAVs to recharge remotely deployed sensors and how we are using very low flying UAVs to monitor the growth of crops.
Biography: Dr. Carrick Detweiler is an Assistant Professor in the Computer Science and Engineering department at the University of Nebraska-Lincoln. He co-directs and co-founded the Nebraska Intelligent MoBile Unmanned Systems (NIMBUS) Lab at UNL, which focuses on developing software and systems for small aerial robots and sensor systems. Carrick obtained his B.A. in 2004 from Middlebury College and his Ph.D. in 2010 from MIT CSAIL. He is a Faculty Fellow at the Robert B. Daugherty Water for Food Institute at UNL and recently received the 2014 College of Engineering Henry Y. Kleinkauf Family Distinguished New Faculty Teaching Award. He is currently lead PI on NSF and USDA grants, including a National Robotics Initiative Grant. In addition to research activities, Carrick actively promotes the use of robotics in the arts through workshops and collaborations with the international dance companies Pilobolus and STREB.
Host: RASC
Location: Ronald Tutor Hall of Engineering (RTH) - 406
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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EE-Electrophysics
Mon, Mar 23, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jesse Maassen, Purdue University
Talk Title: Heat transport on the nanoscale: lessons from electron transport
Abstract: Electronics has shaped our modern world. The downscaling of device dimensions that made this possible not only presented enormous technological challenges, it also raised many fundamental questions. Over the past two decades a deep understanding of electronic transport at the nanoscale has been developed, along with the computational tools that accurately capture the relevant physics. However, electron transport cannot be separated from phonon transport. Self-heating in nanoscale devices critically limits their performance, and coupled electron-phonon transport in nanostructures provides a route to increase the performance of thermoelectric energy conversion. Further progress in electronics will require a deeper understanding of thermal transport at the nanoscale along with the development of new computational tools that address challenges from the nano- to macro-scale. I have begun to tackle these issues in a unique way - by unifying the concepts and techniques for electron and phonon transport.
In this talk I will discuss our recent findings on nanoscale heat transport
- highlighting the similarities of electron and phonon transport. Work on the fundamental limits of thermal interface resistance and transport in 2D materials will be presented. In addition, I will describe a new approach to treat heat transport on all length and time scales. This technique is not only simple, computationally efficient and able to reproduce results of detailed modeling with high accuracy, but is also physically transparent thus providing new fundamental (and still controversial!) insights such as the fact that Fourier's Law often works very well at the nanoscale. Results of this method combined with detailed first principles modeling of nanomaterials will be presented.
We envision using this framework to analyze recent unresolved experiments, to help understand the results of detailed simulations, and to explore coupled electro-thermal transport in a variety nanoscale materials and devices.
Biography: Jesse Maassen received B.Eng. and M.A.Sc. degrees in engineering physics from the Ecole Polytechnique de Montreal in 2006. He obtained a Ph.D. in physics from McGill University in 2011 by working on first principles simulations of nanoelectronic devices. Since 2012 Dr. Maassen has been a postdoctoral research associate at Purdue University working with Prof.
Mark Lundstrom. His research interests focus on exploring novel materials and devices, using predictive first principles modeling, with an emphasis on electro-thermal transport.
Jesse Maassen was awarded a Alexander Graham Bell Canada Graduate Scholarship from the National Sciences and Engineering Research Council
(NSERC) of Canada, as well as a Postdoctoral Fellowship from NSERC. He won best doctoral thesis from McGill Physics Department in 2011, and received the Keren Prize for best theoretical work at the Trends in Nanotechnology conference.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Seminar with Ermah Ergelen
Mon, Mar 23, 2015 @ 04:30 PM - 05:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Emrah Ergelen, Vice President of Arge Construction
Talk Title: Strategic Alliances in Emerging Markets: A Perspective from International Construction Industry
Abstract: The presentation discusses strategic alliances used in the international construction industry, while focusing on reasons, processes, types, success factors and pitfalls in relation to such alliances. The speaker illustrates these topics with specific project examples from his experience in the emerging markets.
Biography: Mr. Emrah Ergelen is an entrepreneur and a professional with a 20-years experience in the international construction industry in Eastern Europe, the Middle East and Northern Africa. He is currently the Vice President of Arge Construction, co-founded by him in 2005 as a spin-off from his family firm Hazinedaroglu, for which he has worked between 1995-2005. During his career Emrah managed 19 strategic alliances, all of which were international. He holds a MBA from Bocconi, a MS in Construction Engineering and Management from MIT and a BEng with Honours in Civil Engineering from Nottingham.
Host: Hank Koffman
More Information: Ermah Poster.pdf
Location: Von Kleinsmid Center For International & Public Affairs (VKC) - 100
Audiences: Everyone Is Invited
Contact: Kaela Berry
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CS Colloquium: Justin Solomon (Stanford University) - Transportation Techniques for Geometric Data Processing
Tue, Mar 24, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Justin Solomon, Stanford University
Talk Title: Transportation Techniques for Geometric Data Processing
Series: CS Colloquium
Abstract: Modeling and understanding low- and high-dimensional data is a recurring theme in graphics, optimization, learning, and vision. Abstracting away application domains reveals common threads using geometric constructs like distances, similarities, and curvatures. This shared structure suggests the possibility of developing geometric data processing as a discipline in itself.
To this end, I will introduce optimal transportation (OT) as a versatile component of the geometric data processing toolkit. Originally proposed for minimizing the cost of shipping products from producers to consumers, OT links probability and geometry using distributions to encode geometric features and developing metric machinery to quantify their relationships.
To transition OT from theory to practice, I will show how to solve previously intractable OT problems efficiently on discretized domains and demonstrate a wide range of applications enabled by this new machinery. I will illustrate the advantages and challenges of OT for geometric data processing by outlining my recent work in geometry processing, computer graphics, and machine learning. In each case, I will consider optimization aspects of the OT problem for relevant geometric domains---including triangulated surfaces, graphs, and subsets of Euclidean space---and then show how the resulting machinery can be used to approach outstanding problems in surface correspondence, modeling, and semi-supervised learning.
This lecture will be streamed HERE.
Biography: Justin Solomon is a PhD candidate and teaching fellow in the Geometric Computing Group at Stanford University studying problems in shape analysis, machine learning, and graphics from a geometric perspective. His work is supported by the Hertz Foundation Fellowship, the NSF Graduate Research Fellowship, and the NDSEG Fellowship. Justin holds bachelors degrees in mathematics and computer science and an MS in computer science from Stanford. He has served as the lecturer for courses in graphics, differential geometry, and numerical methods; his forthcoming textbook entitled Numerical Algorithms focuses on applications of numerical methods across modern computer science. Before his graduate studies, Justin was a member of Pixar's Tools Research group. He is a pianist, cellist, and amateur musicologist with award-winning research on early recordings of the Elgar Cello Concerto.
Host: Computer Science Department
More Info: https://bluejeans.com/301312091/browser
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/301312091/browser
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Electrical Engineering Seminar
Tue, Mar 24, 2015 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Swagath Venkataramani, Purdue University
Talk Title: Addressing the Efficiency Gap with Approximate Computing
Abstract: The âefficiency gapâ created by diminishing benefits from semiconductor technology scaling on the one hand, and projected growth in computing and data demand on the other, has created an urgent need to identify new sources of computing efficiency across the computing stack. Fortunately, the workloads that drive the demand for computing efficiency also present new opportunities. In data centers and the cloud, the demand for computing is driven by the need to organize, search through, analyze, and draw inferences from, exploding amounts of digital data. In mobile and embedded devices, the need to more naturally and intelligently interact with the physical world, and process richer media drive much of the computing demand. A common pattern that emerges from both ends of the spectrum is that these applications are largely not about calculating a precise numerical answer; instead, âcorrectnessâ is defined as producing results that are good enough, or of sufficient quality, to produce an acceptable user experience. As a result, these workloads are endowed with a high degree of intrinsic resilience to their underlying computations being executed in an approximate or inexact manner. Approximate computing broadly refers to exploiting the forgiving nature (or intrinsic resilience) of applications to design more efficient (faster, lower power) computing platforms. In this talk, I will describe how current workload trends are driving interest in approximate computing, and describe a vision for approximate computing at all layers of the computing stack. To realize this vision, I will outline a holistic approach that includes automatic frameworks to synthesize approximate circuit blocks, a model for programmable approximate processors that explicitly codifies the notion of quality into the HW/SW interface, and finally software techniques to systematically identify resilient computations within an application and to apply approximate computing to achieve a favorable quality-efficiency tradeoff. I will conclude with an overview of the other research directions that I am exploring to address the efficiency gap viz. computing with spintronics, and heterogeneous many-core accelerators for emerging workloads.
Biography: Swagath Venkataramani is a 5-year PhD student in the School of Electrical and Computer Engineering, Purdue University. His research interests include, Approximate Computing, Computing with Spintronic Devices, Heterogeneous Parallel Architectures, and Computational Imaging. His dissertation research was awarded the Intel PhD fellowship in computing leadership and Purdue Bilsland Dissertation fellowship. It has also been featured in MIT Technology Review, Slashdot, Physics Today, and NSF News from the Field. Swagath graduated with a Bachelors degree in Electrical and Electronics Engineering from College of Engineering, Guindy, Anna University, India as the university gold medalist. He has worked with the Exa-scale Computing Group at Intel as part of the US DOEâs FastForward Program, and with the Sensing and Energy Research Group at Microsoft Research.
Host: Prof. Alice C. Parker
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Epstein Institute / ISE 651 Seminar Series
Tue, Mar 24, 2015 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Jimeng Sun, Associate Professor, School of Computational Science and Engineering, College of Computing, Georgia Institute of Technology
Talk Title: Computational Phenotyping on Electronic Health Records using Tensor Factorization
Abstract: As the adoption of electronic health records (EHRs) has grown, EHRs are now composed of a diverse array of data, including structured information (e.g., diagnoses, medications, and lab results), and unstructured clinical progress notes. The interactions among different data sources within an EHR are challenging to model, hampering our ability to leverage traditional analytic frameworks.
The goal of this project is to address these challenges by developing a general computational framework for transforming EHR data into meaningful phenotypes with only modest levels of expert guidance. We represent and analyze EHR data as inter-connected high-order relations i.e. tensors (e.g. tuples of patient-medication-diagnosis, patient-lab, and patient-symptoms). The proposed analytic framework generalizes several existing data mining methodologies, including dimensionality reduction, topic modeling and co-clustering, which all arise as limited special cases of analyzing second order tensors. It will also enable flexible refinement of candidates to incorporate feedback from domain experts.
The significance of the resulting phenotypes will have diverse clinical applications, including: a) cohort construction, where case and control patients are identified with respect to specific phenotype combinations; b) genome wide association studies (GWAS), where target phenotypes of patients are tested against DNA sequence variation for significant statistical associations; and c) clinical predictive modeling, where a model is developed to predict target phenotypes or diseases will be demonstrated. The framework is developed with public accessible data from MIMIC-II and CMS and validate in real clinical environments at Northwestern Memorial Hospital and VUMC through several high-impact disease targets (including hypertension, type 2 diabetes, hypothyroidism, atrial fibrillation, rheumatoid arthritis, and multiple sclerosis).
Biography: Jimeng Sun is an Associate Professor of School of Computational Science and Engineering at College of Computing in Georgia Institute of Technology. Prior to joining Georgia Tech, he was a research staff member at IBM TJ Watson Research Center. His research focuses on health analytics using electronic health records and data mining, especially in designing novel tensor analysis and similarity learning methods and developing large-scale predictive modeling systems.
Dr. Sun has worked on various healthcare applications such as computational phenotyping from electronic health records, heart failure onset prediction and hypertension control management. He has collaborated with many healthcare institutions including Vanderbilt university medical center, Children's healthcare of Atlanta, Center for Disease Control and Prevention (CDC), Geisinger Health System and Sutter Health.
He has published over 70 papers, filed over 20 patents (5 granted). He has received ICDM best research paper award in 2008, SDM best research paper award in 2007, and KDD Dissertation runner-up award in 2008. Dr. Sun received his B.S. and M.Phil. in Computer Science from Hong Kong University of Science and Technology in 2002 and 2003, and PhD in Computer Science from Carnegie Mellon University in 2007.
More Information: Seminar-Jimeng Sun.docx
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Viterbi Keynote Lecture
Tue, Mar 24, 2015 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. H. Vincent Poor / Dean, School of Engineering and Applied Science, Princeton University
Talk Title: Fundamental Limits on Information Security and Privacy
Series: Distinguished Lecturer Series
Abstract: As has become quite clear from recent headlines, the ubiquity of technologies such as wireless communications and on-line data repositories has created new challenges in information security and privacy. Information theory provides fundamental limits that can guide the development of methods for addressing these challenges. After a brief historical account of the use of information theory to characterize secrecy, this talk will review two areas to which these ideas have been applied successfully: wireless physical layer security, which examines the ability of the physical properties of the radio channel to provide confidentiality in data transmission; and utility-privacy tradeoffs of data sources, which quantify the balance between the protection of private information contained in such sources and the provision of measurable benefits to legitimate users of them. Several potential applications of these ideas will also be discussed.
Biography: H. Vincent Poor (Ph.D., Princeton 1977) is Dean of the School of Engineering and Applied Science at Princeton University, where he is also the Michael Henry Strater University Professor. From 1977 until he joined the Princeton faculty in 1990, he was a faculty member at the University of Illinois at Urbana-Champaign. He has also held visiting appointments at a number of other universities, including most recently at Stanford and Imperial College. His research interests are primarily in the areas of information theory and signal processing, with applications in wireless networks and related fields. Among his publications in these areas is the recent book Principles of Cognitive Radio (Cambridge University Press, 2013). At Princeton he has developed and taught several courses designed to bring technological subject matter to general audiences, including âThe Wireless Revolutionâ (in which Andrew Viterbi was one of the first guest speakers) and âSix Degrees of Separation: Small World Networks in Science, Technology and Society.â
Dr. Poor is a member of the National Academy of Engineering and the National Academy of Sciences, and is a foreign member of the Royal Society. He is a former President of the IEEE Information Theory Society, and a former Editor-in-Chief of the IEEE Transactions on Information Theory. He currently serves as a director of the Corporation for National Research Initiatives and of the IEEE Foundation, and as a member of the Council of the National Academy of Engineering. Recent recognition of his work includes the 2014 URSI Booker Gold Medal, and honorary doctorates from several universities in Asia and Europe.
Host: Dr. Sandeep K. Gupta
More Info: https://bluejeans.com/770154652
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
Event Link: https://bluejeans.com/770154652
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Electrical engineering seminar
Wed, Mar 25, 2015 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Laurent Lessard, University of California, Berkeley
Talk Title: Automating the analysis and design of large-scale optimization algorithms
Abstract: The next generation of complex engineered systems will see an unprecedented integration of electromechanical components, communication, and embedded computation. Imminent examples include self-driving vehicles, smart buildings, and UAVs for automated delivery of goods. It is critical that these new technologies be safe and efficient, as their failure would be socially and economically catastrophic.
This talk will focus on the challenge of integrating data-driven optimization algorithms into safety-critical control systems. The problem of selecting a suitable algorithm for use in large-scale optimization is currently more of an art than a science; a great deal of expertise is required to know which algorithms to apply and how to properly tune them. Moreover, there are seldom performance or robustness guarantees.
Our key observation is that iterative optimization algorithms may be viewed as discrete-time controllers, and the problem of algorithm selection/tuning may be viewed as a robust control problem. This viewpoint allows us to treat both electromechanical and algorithmic components in a unified manner. By solving simple semidefinite programs, we can derive robust bounds on convergence rates for popular algorithms such as the gradient method, proximal methods, fast/accelerated methods, and operator-splitting methods such as ADMM. Finally, our framework can be used to search for algorithms that meet desired performance guarantees, thus establishing a new and principled methodology for algorithm design. As an illustrative example, we synthesize a new family of first-order algorithms that explore the trade-off between performance and robustness to noise.
Biography: Laurent Lessard was born and raised in Toronto, Canada. He received the B.A.Sc. degree in Engineering Science from the University of Toronto and the M.S. and Ph.D. degrees in Aeronautics and Astronautics from Stanford University. He is currently a postdoctoral scholar in the Berkeley Center for Control and Identification at the University of California, Berkeley. Before that, he was an LCCC postdoc in the Department of Automatic Control at Lund University in Sweden. His research interests include decentralized control, robust control, and large-scale optimization. Dr. Lessard received the O. Hugo Schuck Best Paper Award at the American Control Conference in 2013.
Host: Prof. Rahul Jain
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Communications, Networks & Systems (CommNetS) Seminar
Wed, Mar 25, 2015 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Young-Han Kim, UC San Diego
Talk Title: Point-to-point codes for interference channels: A journey toward high performance at low complexity
Series: CommNetS
Abstract: For high data rates and massive connectivity, the next-generation cellular networks are expected to deploy many small base stations. While such dense deployment provides the benefit of bringing radio closer to end users, it also increases the amount of interference from neighboring cells. Consequently, smart management of interference would become one of the key enabling technologies for high-spectral-efficiency, low-power, broad-coverage wireless communication.
In this talk, we discuss recent developments in channel coding techniques for interference channels, primarily focusing on the sliding-window superposition coding scheme. This coding scheme achieves the performance of simultaneous decoding with point-to-point channel codes and low-complexity decoding. Simulation results demonstrate that sliding-window superposition coding can sometimes double the performance of the conventional method of treating interference as noise, still using the standard LTE turbo codes.
Joint work with Bernd Bandemer, Chiao-Yi Chen, Abbas El Gamal, Hosung Park, Eren Sasoglu, and Lele Wang.
Biography: Young-Han Kim received his B.S. degree in Electrical Engineering from Seoul National University in 1996 and his Ph.D. degree in Electrical Engineering (M.S. degrees in Statistics and in Electrical Engineering) from Stanford University in 2006. Since then, he has been a faculty member in the Department of Electrical and Computer Engineering at the University of California, San Diego. Professor Kim is a recipient of the 2008 NSF CAREER Award and the 2012 IEEE Information Theory Paper Award. He was a Distinguished Lecturer of the IEEE Information Theory Society during 2012 and 13.
Host: Prof. Salman Avestimehr and the Ming Hsieh Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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EE-Electrophysics Seminar
Wed, Mar 25, 2015 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Meisam Honarvar, California Institute of Technology
Talk Title: From Tera-Scale Communication to Lab-in-the-Body: Challenges and Opportunities for CMOS Technology
Abstract: Combining the high level of integration offered by CMOS and micro/nanofabrication technology enables complex and compact sensing systems. During the first part of the presentation, the opportunities for integrated microsystems for implantable health monitors will be explored. The combination of power and data telemetry and physiological sensors within small chips enables us to contemplate new microsystems for healthcare monitoring that serve as closed loop therapy systems and allow for the remote management of patients. Such systems could be implanted as continuous glucose monitors (CGM), neural prosthetics and other metabolic and physiological measurement tools and will enable a new class of continuous digital health monitors that leads to preventative healthcare at lower cost. As an example of such systems, I will present my research on implantable CGM microsystems.
Over the past couple of decades we have witnessed a tremendous growth in computational capability owing to the rapid advances in CMOS technology. Additionally smart devices and their social apps, as well as cloud storage and computation have resulted in a tremendous growth in big data infrastructures. With this increase in the computation, a corresponding scaling in data communication bandwidth is inevitable. The bandwidth of the current physical channels not only limits the communication between chips, it also imposes serious problem for on-chip interconnection. In the second part of my talk, I will go over new low-power circuit techniques that enable massively parallel electrical and optical communication to address the bandwidth requirement of the future networks.
Biography: Meisam Nazari received the M.S. and Ph.D. degrees in electrical engineering from California Institute of Technology, Pasadena in 2009 and 2013, respectively. He is currently a staff scientist in the department of electrical engineering at California Institute of Technology. His research interests include high-performance mixed-signal integrated circuits, with the focus on biomedical and medical circuits and systems as well as high-speed and low-power optical and electrical interconnects. He is the recipient of 2008 Brian L. Barge Award for excellence in microsystems integration, 2010 AMD/CICC Student Scholarship Award, the 2012 Solid-State Circuits Society Pre-doctoral Achievement Award, and the 2012 Circuits and Systems Society Pre-doctoral Scholarship.
Host: EE-Electrophysics
Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Ming Hsieh Institute Distinguished Visitor Seminar
Wed, Mar 25, 2015 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Georgios B. Giannakis , University of Minnesota
Talk Title: Seminar I: Learning Tools for Big Data Analytics
Series: MHI Distinguished Visitor Seminar Series
Abstract: We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internetâs backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. The sheer volume of data makes it often impossible to run analytics using a central processor and storage, and distributed processing with parallelized multi-processors is preferred while the data themselves are stored in the cloud. As many sources continuously generate data in real time, analytics must often be performed âon-the-flyâ and without an opportunity to revisit past entries. Due to their disparate origins, massive datasets are noisy, incomplete, prone to outliers, and vulnerable to cyber-attacks. These effects are amplified if the acquisition and transportation cost per datum is driven to a minimum. Overall, Big Data present challenges in which resources such as time, space, and energy, are intertwined in complex ways with data resources. Given these challenges, ample signal processing opportunities arise. This tutorial lecture outlines ongoing research in novel models applicable to a wide range of Big Data analytics problems, as well as algorithms to handle the practical challenges, while revealing fundamental limits and insights on the mathematical trade-offs involved.
Biography: (Fellowâ97) received his Diploma in Electrical Engr. from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. Since 1999 he has been a professor with the Univ. of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications in the ECE Department, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing subjects on which he has published more than 375 journal papers, 625 conference papers, 20 book chapters, two edited books and two research monographs (h-index 112). Current research focuses on big data analytics, wireless cognitive radios, network science with applications to social, brain, and power networks with renewables. He is the co-iinventor of 22 patents issued, and the co-recipient of 8 best paper awards from the IEEE Signal Processing (SP) and Communications Societies, including the G. Marconi Prize Paper Award in Wireless Communications. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), a Young Faculty Teaching Award, the G. W. Taylor Award for Distinguished Research from the University of Minnesota, and the IEEE Fourier Technical Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in a number of posts including that of a Distinguished Lecturer for the IEEE-SP Society.
Host: Professor Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia Veal
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Energy informatics distinguished seminar
Wed, Mar 25, 2015 @ 03:30 PM - 04:30 PM
Thomas Lord Department of Computer Science, Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Arvind, Massachusetts Institute of Technology
Talk Title: BlueDBM: A Multi-access, Distributed Flash Store for Big Data Analytics
Series: Energy Informatics Distinguished Seminar Series
Abstract: Complex analytics of the vast amount of data collected via social media, cell phones, ubiquitous smart sensors, and satellites is likely to be the biggest economic driver for the IT industry over the next decade. For many âBig Dataâ applications, the limiting factor in performance is often the transportation of large amount of data from hard disks to where it can be processed, i.e. DRAM. We will present BlueDBM, an architecture for a scalable distributed flash store which is designed to overcome this limitation in two ways. First, the architecture provides a high-performance, high-capacity, scalable random-access storage. It achieves high-throughput by sharing large numbers of flash chips across a low-latency, chip-to-chip backplane network managed by the flash controllers. Second, it permits some computation near the data via a FPGA-based programmable flash controller. We will present the preliminary results on accelerating complex queries using BlueDBM consisting of 20 nodes and up to 32 TB of flash.
Biography: Arvind is the Johnson Professor of Computer Science and Engineering at MIT. Arvindâs group, in collaboration with Motorola, built the Monsoon dataflow machines and its associated software in the late eighties. In 2000, Arvind started Sandburst which was sold to Broadcom in 2006. In 2003, Arvind co-founded Bluespec Inc., an EDA company to produce a set of tools for high-level synthesis. In 2001, Dr. R. S. Nikhil and Arvind published the book âImplicit parallel programming in pHâ. Arvind's current research focus is on enabling rapid development of embedded systems.
Arvind is a Fellow of IEEE and ACM, and a member of the National Academy of Engineering and the American Academy of Arts and Sciences.
Host: Viktor Prasanna
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Annie Yu
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CS Colloquium: Suman Jana (Stanford) - Rise of the Planet of the Apps: Security and Privacy in the Age of Bad Code
Thu, Mar 26, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Suman Jana, Stanford
Talk Title: Rise of the Planet of the Apps: Security and Privacy in the Age of Bad Code
Series: CS Colloquium
Abstract: Computing is undergoing a major shift. Third-party applications hosted in online software markets have become ubiquitous on all kinds of platforms: mobile phones, Web browsers, gaming devices, even household robots. These applications often include yet more third-party code for advertising, analytics, etc. These trends have dramatically increased the amount of bad code throughout the software stack - buggy code, malicious code, code that overcollects private information intentionally or by accident, overprivileged code vulnerable to abuse - as well as the amount of sensitive data processed by bad code.
In this talk, I will demonstrate that existing application platforms are ill-suited to dealing with bad code, thus causing security and privacy problems. I will then show how to isolate bad code without affecting its useful functionality, by redesigning the interfaces across the software stack and controlling the information released to the applications by the platform. I will also show how automated testing can identify bad code and help developers improve their applications.
The lecture will be streamed HERE.
Biography: Suman Jana is a postdoctoral researcher at Stanford University. He earned his PhD in 2014 from the University of Texas, where he was supported by the Google PhD Fellowship. He is broadly interested in identifying fundamental flaws in existing systems and building new systems with strong security and privacy guarantees. Suman received the 2014 PET Award for Outstanding Research in Privacy-Enhancing Technologies, Best Practical Paper Award from the 2014 IEEE Symposium on Security and Privacy (Oakland), Best Student Paper Award from the 2012 IEEE Symposium on Security and Privacy, and the 2012 Best Applied Security Paper Award.
Suman's research has been widely covered in popular media, and his code has been deployed at Google, Mozilla, and Apache.
Host: Computer Science Department
More Info: https://bluejeans.com/773593518
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/773593518
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Ming Hsieh Institute Distinguished Visitor Seminar
Thu, Mar 26, 2015 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Georgios B. Giannakis , University of Minnesota
Talk Title: Seminar II: Comprehensive State Inference for Cognitive Radio Networks
Series: MHI Distinguished Visitor Seminar Series
Abstract: Spectrum sensing is a critical prerequisite in envisioned applications of wireless cognitive radio (CR) networks, which promise to resolve the perceived bandwidth scarcity versus under-utilization dilemma. This talk presents recent advances for comprehensive situation awareness at the PHY of CR networks by capitalizing on the novel notion of spatio-temporal RF cartography, which amounts to constructing two families of maps: (m1) global power spectral density maps capturing the distribution of power across space, time, and frequency; and (m2) local channel gain maps providing the propagation medium per frequency from each node to any point in space and time. Paralleling the success of routing tables, the vision is to have CR nodes jointly utilize these maps so as to enable: (v1) identification of opportunistically available spectrum bands for re-use, and handoff operation; (v2) localization, transmit-power estimation, and tracking of primary user activities; and (v3) interference control, resource allocation, and routing. If time allows, CR sensing beyond the PHY will be presented too for flagging network anomalies.
Biography: (Fellowâ97) received his Diploma in Electrical Engr. from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. Since 1999 he has been a professor with the Univ. of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications in the ECE Department, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing subjects on which he has published more than 375 journal papers, 625 conference papers, 20 book chapters, two edited books and two research monographs (h-index 112). Current research focuses on big data analytics, wireless cognitive radios, network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 22 patents issued, and the (co-) recipient of 8 best paper awards from the IEEE Signal Processing (SP) and Communications Societies, including the G. Marconi Prize Paper Award in Wireless Communications. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), a Young Faculty Teaching Award, the G. W. Taylor Award for Distinguished Research from the University of Minnesota, and the IEEE Fourier Technical Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in a number of posts including that of a Distinguished Lecturer for the IEEE-SP Society.
Host: Professor Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia Veal
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RASC Seminar Event: Prof. Carrick Detweiler (University of Nebraska-Lincoln) - Bringing Aerial Robots Closer to the Water: Sensing, Sampling, and Safety
Thu, Mar 26, 2015 @ 12:30 PM - 01:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Carrick Detweiler, University of Nebraska-Lincoln
Talk Title: Bringing Aerial Robots Closer to the Water: Sensing, Sampling, and Safety
Series: RASC Seminar Series
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly being used for everything from crop surveying to pipeline monitoring. They are significantly cheaper than the traditional manned airplane or helicopter approaches to obtaining aerial imagery and sensor data. The next generation of UAVs, however, will do more than simply observe. In this talk, I will discuss the challenges of using aerial robots very close to the water to obtain aerial water samples and sensor data from remote waters locations without needing to bring a boat to each location. When flying close to water, there is little time to react to errors and among obstacles. I will discuss automated software analysis techniques we are developing to detect and correct system errors to reduce risk and increase safety. I will focus on our recent work on the UAV-based water sampler system, but also discuss other applications we are pursuing, including using UAVs to recharge remotely deployed sensors and how we are using very low flying UAVs to monitor the growth of crops.
Biography: Dr. Carrick Detweiler is an Assistant Professor in the Computer Science and Engineering department at the University of Nebraska-Lincoln. He co-directs and co-founded the Nebraska Intelligent MoBile Unmanned Systems (NIMBUS) Lab at UNL, which focuses on developing software and systems for small aerial robots and sensor systems. Carrick obtained his B.A. in 2004 from Middlebury College and his Ph.D. in 2010 from MIT CSAIL. He is a Faculty Fellow at the Robert B. Daugherty Water for Food Institute at UNL and recently received the 2014 College of Engineering Henry Y. Kleinkauf Family Distinguished New Faculty Teaching Award. He is currently lead PI on NSF and USDA grants, including a National Robotics Initiative Grant. In addition to research activities, Carrick actively promotes the use of robotics in the arts through workshops and collaborations with the international dance companies Pilobolus and STREB.
Host: RASC
Location: Ronald Tutor Hall of Engineering (RTH) - 406
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Distinguished Lecture: Yang Jiao (ASU)
Thu, Mar 26, 2015 @ 12:45 PM - 02:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Yang Jiao, Arizona State University, Materials Science & Engineering
Talk Title: A unified scheme for the quantification, modeling, and reconstruction of heterogeneous materials in 3D and 4D
Series: Distinguished Lectures
Abstract: TBA
Host: Prof. Sahimi
Location: James H. Zumberge Hall Of Science (ZHS) - 159
Audiences: Everyone Is Invited
Contact: Ryan Choi
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2015 John Laufer Lecture
Thu, Mar 26, 2015 @ 01:00 PM - 03:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Harry L. Swinney, Sid Richardson Foundation Regents Chair in Department of Physics at College of Natural Sciences at University of Texas at Austin
Talk Title: Internal Gravity Wave Energy in the Oceans
Abstract: Internal gravity waves occur inside fluids whose density varies with depth, as happens in the atmosphere, oceans, and protoplanetary disks. In the oceans the internal waves produced by tidal flow over bottom topography travel thousands of kilometers, affecting ocean mixing and currents, and ultimately impacting the climate. However, it is difficult to make accurate estimates of the total internal wave energy in the oceans because of the complexity of ocean topography and the constructive and destructive interference of the waves. This talk presents results from laboratory experiments, numerical simulations, and ocean observations that yield insight into internal wave dynamics and improve estimates of the total internal wave energy.
Biography: Harry L. Swinney received a BS in physics from Rhodes College (1961) and a PhD in physics from Johns Hopkins University (1968). He held faculty appointments at New York University and City College of New York before moving in 1978 to the University of Texas at Austin. In the 1970s Swinney and J.P. Gollub found that fluid flow between concentric cylinders with the inner one rotating exhibited a transition from flow characterized by two incommensurate frequencies to chaotic flow; this was the first laboratory study of chaotic behavior. Later, at the University of Texas, Swinney showed that the strange (chaotic) attractors that had been discussed by theorists actually occur in laboratory systems. In the past three decades Swinneyâs research group has examined chaos and pattern formation in a variety of fluid, chemical, solid, granular, and biological systems. He was elected to the National Academy of Sciences in 1992. He is a Fellow of the American Physical Society, the American Association for the Advancement of Science, the American Academy of Arts and Sciences, and the Society of Industrial and Applied Mathematics. He was awarded the American Physical Society Fluid Dynamics Prize, the Society of Industrial and Applied Mathematics Moser Lecture Prize, the Lewis Fry Richardson Medal of the European Geophysical Union, and the Boltzmann Medal of the International Union of Pure and Applied Physics.
Location: Ronald Tutor Campus Center (TCC) - Ballroom A
Audiences: Everyone Is Invited
Contact: Valerie Childress
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Electrical Engineering Systems Seminar - Xuehai Qian
Thu, Mar 26, 2015 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Xuehai Qian, Postdoctoral Researcher, University of California Berkeley
Talk Title: Taming Relaxed Memory Consistency and Non-determinism in Parallel Systems
Abstract: With computer architectures moving towards an era dominated by many-core machines and the ever-increasing demands of big data processing, parallel programming has become the norm. Unfortunately, most current programmers find parallelism challenging. It is urgent to provide architectural and software supports to make parallel applications easy to build, reason and debug. Among others, relaxed memory consistency and non-determinism in particular make shared-memory based parallel programming difficult.
In this talk, I will give an overview of our strategy to tame the two factors. Specifically, I will present OmniOrder, a cache coherence protocol for atomic blocks (transactions). It eliminates the effects of relaxed consistency by supporting strict sequential consistency with high performance. OmniOrder supports conflict serialization based on the conventional directory-based protocol. I will also present Pacifier, a deterministic record and replay scheme for relaxed consistency models beyond Total-Store-Order (TSO). It helps to track and understand the behaviors of relaxed consistency.
Biography: Xuehai Qian is a postdoctoral researcher at University of California Berkeley. He got the Ph.D. from the Department of Computer Science at the University of Illinois, Urbana-Champaign in 2013. His research interests include parallel computer architecture, architectural support for programming productivity and debugging support for large-scale HPC applications. He received an MS in Computer Science from the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), and a BS in Computer Engineering from Beihang University, Beijing.
Host: Prof. Michel Dubois
More Information: print_Qian.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
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USC PSOC Seminar Series - Dr. Min Yu
Fri, Mar 27, 2015 @ 11:45 AM - 01:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Min Yu, MD/PhD, USC - Keck School of Medicine
Talk Title: Circulating tumor cells as liquid biopsies for metastasis
Abstract: Circulating tumor cells (CTCs), shed from primary and metastatic tumors into blood stream, contain potential rare cancer stem cells or metastasis-initiating cells. We have analyzed characteristics of CTCs in both mouse cancer models and human cancer patients. Previously, we have discovered an important WNT2-TAK1 pathway in promoting pancreatic cancer metastasis via enhanced resistance to anoikis, and demonstrated evidence of epithelial mesenchymal transition (EMT) in CTCs isolated from breast cancer patients. We have recently developed in vitro culture of CTCs, enabling in depth analysis of their molecular properties using next-generation sequencing and pilot drug sensitivity testing. In several CTC lines, inoculation of 20,000 cells into immunodeficient mice was sufficient for tumorigenesis. Thus, patient-derived CTC lines allow detailed interrogation of cancer stem cell properties at single cell level and its derived clonal populations, potentially contributing to the development of targeted therapies against the metastasis initiating cancer stem cells.
Host: USC PSOC - Dr. Mitchell Gross
Location: Clinical Science Center (CSC) - Harkness Auditorium, 2nd Floor
Audiences: Everyone Is Invited
Contact: Rosa Rangel
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W.V.T. Rusch Engineering Honors Colloquium
Fri, Mar 27, 2015 @ 01:00 PM - 02:00 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
Conferences, Lectures, & Seminars
Speaker: Rustom Jehangir, Co-Founder and Engineer, BlueRobotics
Talk Title: Starting a Hardware Company
Host: W.V.T. Rusch Engineering Honors Program
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Jeffrey Teng
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Integrated Systems Seminar
Fri, Mar 27, 2015 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hesaam Esfandyarpour, GenapSys Inc.
Talk Title: TBD
Series: Integrated Systems Seminar
Host: Hosted by Prof. Hossein Hashemi, Prof. Mike Chen, and Prof. Mahta Moghaddam Organized and hosted by Run Chen
More Info: http://mhi.usc.edu/events/event-details/?event_id=915368
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Elise Herrera-Green
Event Link: http://mhi.usc.edu/events/event-details/?event_id=915368
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Mar 27, 2015 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Subhayan De and Simin Karvigh , Astani CEE Ph.D. Candidates
Talk Title: Efficient Bayesian Model Selection for Locally Nonlinear Systems incorporating Dynamic Measurements
Abstract: Subhayan De's abstract:
The modeling of a structural system is often complicated by the dynamic characterization of a component by competing families of models, also known as model classes, where the choice of a particular model class falls to the discretion of the researcher. Bayesian model selection can be used to help find the most plausible model class. For linear models, the computational effort for characterization of dynamic properties using natural frequencies and mode shapes, as well as Monte Carlo sampling method, is reasonably well understood. On the other hand, to characterize the dynamic behavior of nonlinear models, response time histories are needed, resulting in high computational cost even when most of the structure is linear and the nonlinear behavior is very localized.
In this study, the computational effort of Bayesian model selection is dramatically reduced in two ways: (1) using a more intelligent Monte Carlo sampling and (2) exploiting the local nature of the nonlinearities. The marginal likelihoods, which are the evidences of the model classes, are estimated with response time histories using ânested samplingâ (Skilling 2006), which samples more from regions with high likelihood values than regions with low likelihood regions. The localized nature of the nonlinearities in the dynamic system is exploited using an efficient response calculation algorithm (Gaurav et al. 2011) by transforming the system equations of motion to a low-order nonlinear Volterra integral equation (NVIE) that is solved numerically. This approach is demonstrated with numerical models of a base-isolated 11-story 2-bay 99-DOF superstructure on the hysteretic lead rubber bearing (LRB) isolators. Model selection is performed to choose from among six model classes: four linear (AASHTO, CALTRANS, JPWRI, modified AASHTO) and two nonlinear (Bouc-Wen, bilinear) models of the isolator, using simulated responses to historical earthquake records. The computational efficiency of the proposed approach is compared with a traditional ordinary differential equation solver (MATLABâs ode45) demonstrating speedup up to two orders of magnitude.
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Power Grid Voltage Stability and Distributed Control
Mon, Mar 30, 2015 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: John W. Simpson-Porco, University of California Santa Barbara
Talk Title: Power Grid Voltage Stability and Distributed Control
Abstract: Technological and regulatory advances are driving the transition of the electric power grid from a hierarchical, centrally-managed physical system to a decentralized cyber-physical system. While distributed generation and demand response offer lower carbon emissions and energy costs, the deployment of these technologies is increasingly eroding the already thin stability margins of our aging power delivery infrastructure.
This talk addresses these technological challenges in two parts. We first present distributed controllers for frequency and voltage regulation in inverter-based islanded power grids. Our physically intuitive control strategies fuse classic power systems intuition with ideas from multi-agent systems, resulting in plug-and-play, provably stable designs. Under minimal connectivity requirements, communication among the inverter units allows for the recovery of centralized control performance using only localized measurements. We present theoretical and experimental results validating our designs.
In the second part of the talk, we explore more deeply the fundamental properties of AC power flow. Despite decades of research, little analytical understanding exists regarding the solution space of these crucial nonlinear equations, leaving exhaustive numerics as the only reliable option to assess grid operability. Here we present a sharp, closed-form condition which guarantees the existence of a unique high-voltage power flow equilibrium. Our key idea is to explicitly combine the complex structure of the network with the size and locations of power demands, leading to sharp estimates of grid voltage stability margins. We highlight applications of our condition to on-line voltage stability assessment and stability margin-enhancing feedback control.
Biography: John W. Simpson-Porco is a Ph.D. Candidate in the Department of Mechanical Engineering at the University of California Santa Barbara. He received his B.Sc. degree in Engineering Physics from Queen's University in 2010. Mr. Simpson-Porco is a recipient the Automatica Best Paper Prize, the National Sciences and Engineering Research Council of Canada Fellowship, and the Center for Control, Dynamical Systems and Computation Outstanding Scholar Fellowship. His research interests are centered on the stability and control of multi-agent systems and complex dynamic networks, with a focus on modernized electric power grids.
Host: Petros Ioannou, ioannou@usc.edu, EEB 200B, x04452
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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Seminar in Biomedical Engineering
Mon, Mar 30, 2015 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Andrew Laine, PhD, Professor of Biomedical Engineering, Chair of Biomedical Engineering (Columbia University)
Talk Title: QUANTITATIVE IMAGING INFORMATICS IN COST EFFECTIVE PET IMAGING AND CLASSIFICATION OF LUNG DISEASEâ
Abstract: âQUANTITATIVE IMAGING INFORMATICS IN
COST EFFECTIVE PET IMAGING AND
CLASSIFICATION OF LUNG DISEASEâ
Andrew F. Laine, D.Sc.
Percy K. and Vida L.W. Hudson Professor of Biomedical Engineering
Professor, Department of Radiology (Physcis)
Chair, Department of Biomedical Engineering
Columbia University, New York, NY
USA
This talk presents a novel method for emphysema quantification, based on parametric modeling of intensity distributions in the lung and a hidden Markov measure field model to segment emphysematous regions. The framework adapts to the characteristics of an image to ensure a robust quantification of emphysema under varying CT imaging protocols and differences in parenchymal intensity distributions due to factors such as inspiration level. Compared to standard approaches, the present model involves a larger number of parameters, most of which can be estimated from data, to handle the variability encountered in lung CT scans. The method was used to quantify emphysema on a cohort of 87 subjects, with repeated CT scans acquired over a time period of 8 years using different imaging protocols. The scans were acquired approximately annually, and the data set included a total of 365 scans. The results show that the emphysema estimates produced by the proposed method have very high intra-subject correlation values. By reducing sensitivity to changes in imaging protocol, the method provides a more robust estimate than standard approaches. In addition, the generated emphysema delineations promise great advantages for regional analysis of emphysema extent and progression, possibly advancing disease subtyping, including COPD.
An important tool for studying brain disorders is positron emission tomography (PET), a nuclear imaging technology that allows for the in vivo functional characterization and quantification of blood flow, metabolism, protein distribution, and drug occupancy using radioactively tagged probes (tracers). Full quantification of PET images requires invasive arterial input function (AIF) measurement through online arterial blood sampling for the duration of the scan (1-2 hours). The AIF is used to correct images by accounting for the tracer bioavailability, which depends on an individual's physiological capacity for clearance, distribution and metabolism of the tracer. However, AIF measurement is invasive, risky, time consuming, uncomfortable for patients, and costly. Perhaps most importantly, it is impractical at the point-of-care and therefore limits clinical utility of PET. We believe an integrative multi-modal approach is possible via the amount of personalized information about the physiological and biochemical makeup of individuals available in their electronic health record (EHR). This talk will outline a novel approach to combine EHR and dynamic PET imaging data in an optimization framework based on simulated annealing to non-invasively estimate the AIF. Techniques that will be outlined are applicable across imaging modalities, organs and diseases, such as functional imaging of prostate cancer images where increasingly more complex tracers are utilized for assessment and require AIF measurement.
Biography: Andrew F. Laine, D.Sc.
BIO-SKETCH
Andrew F. Laine received his D.Sc. degree from Washington University (St. Louis) School of Engineering and Applied Science in Computer Science, in 1989 and BS degree from Cornell University (Ithaca, NY). He was a Professor in the Department of Computer and Information Sciences and Engineering at the University of Florida (Gainesville, FL) from 1990-1997. He joined the Department of Biomedical Engineering in 1997 and served as Vice Chair of the Department of Biomedical Engineering at Columbia University since 2003 - 2011. He is currently Chair of the Department of Biomedical Engineering and Director of the Heffner Biomedical Imaging at Columbia University and the Percy K. and Vida L. W. Hudson Professor of Biomedical Engineering and Professor of Radiology (Physics). He is a Fellow of IEEE and AIMBE, and he is currently the President of IEEE EMBS (Engineering in Biology and Medicine Society).
Professor Laine is a leader in medical imaging, image analysis and signal processing, computational biology, and biometrics research. He was the first to apply multi-resolution representations for feature analysis of digital mammography and cardiac ultrasound. He pioneered work on medical imaging that he first introduced in 1992 using nonlinear processing techniques of wavelet representations for contrast enhancement. He currently analyzes real-time video 3-D ultrasounds of the heart in an effort to better understand and treat heart disease. He is developing software that will measure the strain on the muscles of the heart in real-time 3-D and localize infarcted or ischemic tissue that could be salvaged by intervention, thus recognizing at an early stage what tissue is damaged or at risk. Director of the Heffner Biomedical Imaging Laboratory at Columbia Engineering, Laine holds two patents related to 3-D processing of ultrasound, has authored more than 300 peer-reviewed papers, and has graduated more than 25 doctoral students in the field of medical image analysis.
Host: Stanley Yamashiro
Location: OHE 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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CS Colloquium: Rong Ge (Microsoft Research) - Towards Provable and Practical Machine Learning
Tue, Mar 31, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rong Ge, Microsoft Research
Talk Title: Towards Provable and Practical Machine Learning
Series: CS Colloquium
Abstract: Many problems --- especially machine learning problems like sparse coding or topic modeling --- are hard in the worst-case, but nevertheless solved in practice by algorithms whose convergence properties are not understood. In this talk I will show how we can identify natural properties of "real-life" instances that allow us to design scalable algorithms for a host of well-known machine learning problems. Most of the talk will be focused on the sparse coding problem: a basic task in many fields including signal processing, neuroscience and machine learning where the goal is to learn a basis that enables a sparse representation of a given set of data, if one exists. Here we give a general framework for understanding alternating minimization which we leverage to analyze existing heuristics and to design new ones also with provable guarantees.
The lecture will be available to stream Here
Biography: Rong Ge obtained his Ph.D. at Princeton University, advised by Sanjeev Arora. Currently he is a post-doctoral researcher at Microsoft Research, New England. He is broadly interested in theoretical computer science and machine learning, especially applying algorithm design and analysis techniques to machine learning problems. The key thread running through his work is to identify natural properties of "real-life" instances that allow him to design scalable algorithms for several interesting machine learning problems including topic modeling and sparse coding.
Host: Computer Science Department
More Info: https://bluejeans.com/651721928
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/651721928
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Epstein Institute / ISE 651 Seminar Series
Tue, Mar 31, 2015 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Soomin Lee, Postdoctoral Associate, Mechanical Engineering and Materials Science, Duke University
Talk Title: Decentralized Optimization for Network Systems
Series: Epstein Institute Seminar Series
Abstract:
We witness a growing interest in distributed multi-agent systems. The Internet, electric power systems, mobile communication networks, and social networks are just a few examples of the myriad network systems that have become a part of everyday life for many people. Lots of interesting optimization problems arise in such network systems. The agents on these networks are geographically distributed, so there is no data fusion center that can see the problem as a whole, gather the information globally, or synchronize actions. Furthermore, the network agents might have varying restrictions on energy, data storage and computational capabilities. In this talk, I will present efficient static and online decentralized optimization algorithms for such systems that allow the network agents to achieve provable consensus to the global optimum. Applications of the algorithms in various engineering disciplines, future vision and possible extension of this work will be discussed as well.
Biography: Dr. Soomin Lee is currently working as a Postdoctoral Associate in Mechanical Engineering and Materials Science at Duke University. She received her Ph.D. in Electrical and Computer Engineering from the University of Illinois, Urbana-Champaign (2013). She received two master's degrees from the Korea Advanced Institute of Science and Technology in Electrical Engineering, and from the University of Illinois at Urbana-Champaign in Computer Science. In 2009, she was an assistant research officer at the Advanced Digital Science Center (ADSC) in Singapore. Her research interests include theoretical optimization, control and optimization of various distributed engineering systems interconnected over complex networks, risk-averse modeling of multiagent robotic systems under dynamically changing and uncertain environments.
More Information: Seminar-Lee_Soomin.docx
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
