Select a calendar:
Filter April Events by Event Type:
SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for April
-
EE-EP Faculty Candidate, Marina Radulaski, Monday, April 2nd at 12pm in EEB 132
Mon, Apr 02, 2018 @ 12:00 PM - 01:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Marina Radulaski, Stanford University
Talk Title: Scalable Nanophotonics for Quantum and Classical Information Processing
Abstract: Technological commodities of the 21st century come with exponential demands on information processing. While the electronic devices face physical limits of scalability, nanophotonics emerges as a leading solution for the Big Data manipulation. In the first part of the seminar, I will discuss the role of novel photonic architectures and robust device design algorithms in meeting the short-term classical hardware speedup goals. Moving toward the implementation of quantum information processing paradigms, I will evaluate applicability of color centers in silicon carbide and diamond to quantum computing, communication and cryptography. Finally, I will present advances in integration of color centers with nanoscale photonic devices serving as efficient quantum bits and quantum light sources.
Biography: Marina Radulaski is a Nano- and Quantum Science and Engineering Postdoctoral Fellow at Stanford University's Ginzton Laboratory. She obtained a PhD in Applied Physics from Stanford University under the supervision of Prof. Jelena Vuckovic, a BSc/MSc in Physics from the University of Belgrade, Serbia, and a BSc/MSc in Computer Science from the Union University, Serbia. Marina was selected among the Rising Stars in EECS in 2017, Stanford Graduate Fellows 2012-2014, and Scientific American's "30-Under-30 Up and Coming Physicists" in 2012. She has performed research internationally at Berkeley Lab, Hewlett-Packard Labs, Oxford University, IQOQI Vienna, Helmholtz Center Berlin, and more. In addition to research, Marina enjoys building communities and promoting science through podcasts, videos and festivals.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
-
Biomedical Engineering Seminars
Mon, Apr 02, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Kathy Nightingale, PhD, Professor, Duke University
Talk Title: Ultrasonic Elasticity Imaging with Acoustic Radiation Force
Abstract: Elasticity imaging involves introducing a mechanical tissue perturbation, imaging the resulting tissue response, and generating images that reflect the underlying mechanical properties of the tissue. Acoustic radiation force impulse (ARFI) based ultrasonic elasticity imaging methods have become widely available in the clinical market over the past five years. To date, these methods have found success clinically in the context of hepatic fibrosis staging and breast lesion characterization, with many additional applications under investigation. A major focus our laboratory has been the development and implementation of high resolution ARFI elasticity imaging methods for prostate cancer imaging and treatment guidance, with initial in vivo findings demonstrating that ARFI imaging is specific for clinically significant prostate cancer. Commercially available ARFI methods that evaluate shear wave propagation to provide quantitative stiffness estimates generally assume that the tissues are linear, isotropic, elastic, homogeneous, and incompressible in order to reconstruct the underlying material stiffness. Our recent work in shear wave imaging focuses on understanding the sources of error in these systems, and developing methods that address some of the underlying assumptions, i.e. using 3D volumetric imaging to analyze material anisotropy, using multi-dimensional filters and two and three dimensional shear wave monitoring to improve image quality in structured media, and exploring different approaches to estimate shearwave dispersion. In this talk, I will review the underlying physics and discuss the promise and limitations of these methods.
Biography: Dr. Nightingale is the James L. and Elizabeth M. Vincent Professor of Biomedical Engineering at Duke University, and she is the director of the Duke Medical Imaging Training Program. Her research interests include ultrasonic and elasticity imaging and instrumentation. She has pioneered the development and clinical translation of acoustic radiation force based elasticity imaging techniques. She is the author of over 75 peer-reviewed journal articles in the areas of ultrasound and elasticity imaging, and has been awarded 9 patents. She has been a recipient of the Klein Family Distinguished Teaching Award, and the Marion Capers Distinguished Research and Teaching Award at Duke University. She has served on numerous NIH and DOD review panels and is currently a charter member of the BMIT-B NIH study section. She is an Associate Editor for Ultrasonic Imaging, a senior member of IEEE, and a fellow of the American Institute of Medical and Biological Engineering.
Host: Professor Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
-
Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Apr 02, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: TBA, TBA
Talk Title: TBA
Series: Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: TBA
Biography: TBA
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
-
EE Seminar - Robust Model-Free Control, Optimization, and Learning in Cyber-Physical Societal Systems
Mon, Apr 02, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jorge I. Poveda, University of California, Santa Barbara
Talk Title: Robust Model-Free Control, Optimization, and Learning in Cyber-Physical Societal Systems
Abstract: The deployment of advanced real-time control and optimization strategies in socially-integrated engineering systems could significantly improve our quality of life while creating jobs and economic opportunity. However, in cyber-physical systems such as smart grids, transportation networks, healthcare, and robotic systems, there still exist several challenges that prevent the implementation of intelligent control strategies. These challenges include the existence of limited communication networks, dynamic environments, multiple decision makers interacting with the system, and complex hybrid dynamics emerging from the feedback interconnection of physical processes and computational devices. In this talk, I will present a set of tools for the analysis and design of model-free feedback mechanisms that can cope with these challenges, and that are suitable for the real-time control and optimization of cyber-physical societal systems. The first part of the talk will focus on the problem of designing a class of robust model-free adaptive pricing mechanisms for systems such as the smart grids, transportation networks, and the Internet, where users behave in a selfish way, and where the objective of the social planner is to maximize the total welfare of the system. Next, I will show that this problem belongs to a broader family of model-free extremization problems, and I will present a general framework for the design of a family of algorithms that can successfully optimize the performance of cyber-physical systems having unknown mathematical models. Finally, I will illustrate how these results can be extended to achieve distributed control of large-scale autonomous systems by implementing novel robust coordination and synchronization feedback mechanisms. The talk will finish by discussing some future directions and preliminary results in the areas of data-driven hybrid control and security in stochastic learning dynamics.
Biography: Jorge I. Poveda is a Ph.D. Candidate at the Center for Control, Dynamical Systems, and Computation (CCDC) at the University of California, Santa Barbara. He received the B.S. degrees in Electronics Engineering and Mechanical Engineering in 2012, and the M.S. degree (Magna Cum Laude) in Electrical Engineering in 2013, all from University of Los Andes, Bogota, Colombia, and the M.S. degree in Electrical and Computer Engineering from the University of California, Santa Barbara, USA, in 2015. He was a Research Intern with the Mitsubishi Electric Research Laboratories in Cambridge, MA, during the summers of 2016 and 2017. He received the 2013 CCDC Outstanding Scholar Fellowship at UCSB, and was a finalist for the Best Student Paper Award at the 56th IEEE Conference on Decision and Control in 2017. His main research interests lie at the intersection of robust feedback control theory, adaptive control, online optimization, and game theory, with applications to cyber-physical and societal systems.
Host: Ashutosh Nayyar, ashutosn@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Series of Lectures
Tue, Apr 03, 2018 @ 10:00 AM - 12:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Thanasis Fokas,
Talk Title: New development in unified transform (Fokas Method, www.wikipedia.org/wiki/Fokas_method).
Abstract: Prof Fokas will give a series of lectures on new development in unified transform (Fokas Method, www.wikipedia.org/wiki/Fokas_method) including applications in water waves with moving boundaries, elliptic PDEs in curved domains and PDEs with variable coefficients. The first two lectures will be in KAP 209 Tuesday, April 3, 2018.
Session #1: from 10am to Noon
Session #2: from 3pm to 5pm
Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
-
Epstein Institute Seminar, ISE 651
Tue, Apr 03, 2018 @ 11:00 AM - 12:00 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Sham Kakade, Associate Professor, University of Washington
Talk Title: Accelerating Stochastic Gradient Descent for Convex and Non-Convex Optimization
Host: Dr. Meisam Razaviyayn
More Information: April 3, 2018_Kakade.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
CS Colloquium: Nicolas Papernot (Pennsylvania State University) - Characterizing the Space of Adversarial Examples in Machine Learning
Tue, Apr 03, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Nicolas Papernot, Pennsylvania State University
Talk Title: Characterizing the Space of Adversarial Examples in Machine Learning
Series: CS Colloquium
Abstract: There is growing recognition that machine learning (ML) exposes new security and privacy vulnerabilities in software systems, yet the technical community's understanding of the nature and extent of these vulnerabilities remains limited but expanding. In this talk, I explore the threat model space of ML algorithms, and systematically explore the vulnerabilities resulting from the poor generalization of ML models when they are presented with inputs manipulated by adversaries. This characterization of the threat space prompts an investigation of defenses that exploit the lack of reliable confidence estimates for predictions made. In particular, we introduce a promising new approach to defensive measures tailored to the structure of deep learning. Through this research, we expose connections between the resilience of ML to adversaries, model interpretability, and training data privacy.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Nicolas Papernot is a PhD student in Computer Science and Engineering working with Professor Patrick McDaniel at the Pennsylvania State University. His research interests lie at the intersection of computer security, privacy and machine learning. He is supported by a Google PhD Fellowship in Security and received a best paper award at ICLR 2017. He is also the co-author of CleverHans, an open-source library widely adopted in the technical community to benchmark machine learning in adversarial settings. In 2016, he received his M.S. in Computer Science and Engineering from the Pennsylvania State University and his M.S. in Engineering Sciences from the Ecole Centrale de Lyon.
Host: Aleksandra Korolova
Location: Olin Hall of Engineering (OHE) - 100D
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
EE Seminar - Embracing Uncertainty: from Differential Privacy to Generative Adversarial Privacy
Tue, Apr 03, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Peter Kairouz, Postdoctoral Scholar, Stanford University
Talk Title: Embracing Uncertainty: from Differential Privacy to Generative Adversarial Privacy
Abstract: The explosive growth in connectivity and data collection is accelerating the use of machine learning to guide consumers through a myriad of choices and decisions. While this vision is expected to generate many disruptive businesses and social opportunities, it presents one of the biggest threats to privacy in recent history. In response to this threat, differential privacy (DP) has recently surfaced as a context-free, robust, and mathematically rigorous notion of privacy.
The first part of my talk will focus on understanding the fundamental tradeoff between DP and utility for a variety of learning applications. Surprisingly, our results show the universal optimality of a family of extremal privacy mechanisms called staircase mechanisms. While the vast majority of early works on DP have focused on using the Laplace mechanism, our results indicate that it is often strictly suboptimal and can be replaced by a staircase mechanism to improve utility. Our results also show that the strong privacy guarantees of DP often come at a significant loss in utility.
The second part of my talk is motivated by the following question: can we exploit data statistics to achieve a better privacy-utility tradeoff? To address this question, I will present a novel context-aware notion of privacy called generative adversarial privacy (GAP). GAP leverages recent advancements in generative adversarial networks (GANs) to arrive to a unified framework for data-driven privacy that has deep game-theoretic and information-theoretic roots. I will conclude my talk by showcasing the performance of GAP on real life datasets.
Biography: Peter Kairouz is a postdoctoral scholar at Stanford University. He received his PhD in ECE from the University of Illinois at Urbana-Champaign (UIUC). He interned twice at Qualcomm and more recently at Google where he designed privacy-aware machine learning algorithms. He is the recipient of the 2015 ACM SIGMETRICS Best Paper Award, the 2012 Roberto Padovani Scholarship from Qualcomm's Research Center, and the 2016 Harold L. Olesen Award for Excellence in Undergraduate Teaching from UIUC. His research interests are interdisciplinary and span the areas of data and network sciences, privacy-preserving data analysis, machine learning, and information theory.
Host: Keith Chugg, chugg@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Epstein Institute Seminar, ISE 651
Tue, Apr 03, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Christopher Williams, Associate Professor, Virginia Tech
Talk Title: Additive Manufacturing of Multifunctional Products via Tailored Materials and Topologies
Host: Dr. Yong Chen
More Information: April 3, 2018_Williams.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
Robust Classification and Change Detection for Brain-Computer Interfaces
Wed, Apr 04, 2018 @ 02:00 AM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Vahid Tarokh, Duke University
Talk Title: Robust Classification and Change Detection for Brain-Computer Interfaces
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: In this talk, we will first discuss eye movement decoding in a working memory experiment involving a macaque monkey. Our objective is to use the local field potentials (LFPs) collected from the brain of the monkey to decode the type of task that the monkey is doing, and the direction of saccade in each task. We will show that the LFP time-series data can be modeled using a nonparametric regression framework, and show that the classifiers trained using minimax function estimators as features are robust and consistent. We will also discuss application of the resulting classifier to the brain data.
We will then briefly discuss the problem of change detection apply it to spike data from a mice experiment collected using cues and electric shocks.
This is a joint work with Taposh Banerjee.
Biography: Vahid Tarokh is Rhodes Family Professor of Electrical and Computer Engineering, Professor of Mathematics, and Computer Science at Duke University. He worked at AT&T Labs-Research until 2000, and subsequently at MIT (as an Associate Professor of EECS) until 2002. He joined Harvard University as Perkins Professor of Applied Mathematics and Hammond Vinton Hayes Senior Fellow of Electrical Engineering. He then joined Duke University in January 2018. His current research focuses on statistical signal processing and applications. Dr. Tarokh has received a number of awards, and holds four honorary degrees.
Host: Prof. Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
-
System Engineering Research Center (SERC) Talks
Wed, Apr 04, 2018 @ 10:00 AM - 11:00 AM
Systems Architecting and Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Robin Yeman, Lockheed Martin Fellow
Talk Title: How do Agile Methods Reduce Risk Exposure and Improve Security on Highly-Critical Systems
Series: SERC Talks
Abstract: With each passing year software continues to grow and every industry regardless of their product uses software as an integral part of their value stream. That phenomenon is especially true in the government space where we deliver highly- critical systems such as aircraft, unmanned systems, missiles & guided weapons, and human space flight vehicles. Highly regulated environments not only require high quality low risk deliveries; they need to be secure. I believe using Agile methods will provide exactly that.
Depending on individual experiences and varying context some projects continue to see Agile methods as risky however various studies and journals such as IEEE have shown Agile methods to deliver results in areas of quality, cost, and schedule across the commercial and government industries. Agile practices can be leveraged to improve the level of security in our systems and reduce our risk exposure while the Internet of Things (IoT) continues to expand our system attack surfaces. In this presentation, we will discuss
• The difference between Agile and traditional Waterfall
• How Agile practices enable security to be embedded in our systems from the start
• Where security is inserted throughout all stages of the SDLC
• Define the art of the possible for the future.
SERC Talks is an open forum discussion series featuring researchers from our community sharing their insights on various questions relevant to Systems Engineering (SE) and its evolution. Dr. Barry Boehm is our Editor-in-Chief of the series, curating the Talks. We encourage your input and insights during these lively discussions online as we strive to create an ongoing and more collaborative dialogue between academia, government and industry sectors of the SE community.
Biography: Robin Yeman works for Lockheed Martin (LM) Information Systems and Global Solution in Northern Virginia as a Lockheed Martin Fellow. She has over 23 years of experience in software and IT, across multiple business areas building everything from Satellites to Submarines. She has been actively supporting and leading Agile programs at Scale both domestically and internationally for the last 15 years with multiple certifications including Scaled Agile Program Consultant, Certified Enterprise Coach (CEC), CSP, CSM, CSPO, PSM, PMP, PMI-ACP, INCOSE Certified Systems Engineer, and ITIL Practitioner. She actively coaches and trains teams through in person coaching, Agile workshops, virtual training classes. She leads the Lockheed Martins Agile Community of Practice and Center of Excellence, speaks at multiple conference engagements each year. Robin received her Masters Degree in Software Engineering from Rensselaer Polytechnic Institute.
Host: Prof. Barry Boehm for the Systems Engineering Research Center
More Info: http://www.sercuarc.org/events/serc-talks-how-do-agile-methods-reduce-risk-exposure-and-improve-security-on-highly-critical-systems/
Webcast: Event Password: SERCLocation: Online via WebEX
WebCast Link: Event Password: SERC
Audiences: Everyone Is Invited
Contact: James Moore II
-
2018 Cornelius Pings Lecture
Wed, Apr 04, 2018 @ 11:00 AM - 12:00 PM
Mork Family Department of Chemical Engineering and Materials Science, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Charles Fairhurst, Professor Emeritus, University of Minnesota
Talk Title: Earth Resources Engineering - An Emerging Field
Series: Pings Keynote Lecture Series
Abstract: The term Earth Resource Engineering was Introduced by the US National Academy of Engineering in 2006 to encompass the traditional extractive discIplines of Petroleum, Mining and Geological Engineering plus newer applications - such as long-term isolation of high-level nuclear waste. This
recognized the unique ability of the rock subsurface to isolate the biosphere from toxic contaminants for millennia. A considerable number of additional uses. both shallow and deep. have since been introduced and/or proposed. These will be described briefly. The lecture will focus on some of the specific challenges in mechanics arising in rock engineering. Evolving over several billion years. the
structural make-up of the subsurface is far more complex than materials encountered in most other branches of engineering. This dictates a different engineering methodology. Thus. although continuum mechanics plays a valuable role in rock engineering, discontinuities, anisotropy, and heterogeneity -Iarge and small scale- must be recognized and considered.
A few examples, including efforts to increase advance rates in tunneling "by a factor of ten". will be provided to illustrate the challenges, and the potential for interdisciplinary collaboration. Introduction of Earth Resource Engineering programs at leading research universities would stimulate such collaboration and advances.
MEET & GREET RECEPTION
HED 1st Floor Lobby
10AM
Host: Professor and Chair Richard Roberts
More Information: USC-2018PingsLecture.pdf
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Breanne Grady
-
Aerospace and Mechanical Engineering Seminar
Wed, Apr 04, 2018 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Alex H. Barnett, Group Leader, Numerical Algorithms, Center for Computational Biology Flatiron Institute (Simons Foundation), New York, NY
Talk Title: Building a Better Nonuniform Fast Fourier Transform
Abstract: The NUFFT allows Fourier analysis of data on non-uniform points at close-to-FFT speeds. It has many applications in science and engineering. I will explain what happens "under the hood" in our new implementation (FINUFFT). This includes 1) a simpler spreading kernel that accelerates run-times for the same accuracy, while preserving a rigorous error analysis, and 2) smart multi-threading. Along the way we will discover how the nationally known bluegrass fiddler Tex Logan fits into the story. Joint work with Jeremy Magland.
Biography: Alex Barnett is an applied mathematician and numerical analyst. He was a faculty member in the mathematics department at Dartmouth College for 12 years, becoming a full professor in 2017. He obtained his Ph.D. in physics at Harvard University, followed by a postdoctoral fellowship in radiology at Massachusetts General Hospital and a Courant Instructorship at New York University. His research interests include scientific computing, partial differential equations, integral equations, biomedical imaging, neuroscience, inverse problems and quantum chaos. Barnett is well known for numerical work in wave scattering, high-frequency eigenvalues, potential theory, periodic geometries and fast algorithms. He has received several grants from the National Science Foundation, and Dartmouth's Karen E. Wetterhahn Memorial Award for Distinguished Creative or Scholarly Achievement.
Host: Department of Aerospace and Mechanical Engineering
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
-
CAIS Seminar: Dr. Paul Rosenbloom (USC) – A Cognitive Architectural Perspective on the Past, Present and Future of AI
Wed, Apr 04, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Paul Rosenbloom, USC
Talk Title: A Cognitive Architectural Perspective on the Past, Present and Future of AI
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: In this talk Dr. Rosenbloom will briefly introduce and explore the notion of a cognitive architecture, as a hypothesis about the fixed structures that define a mind and yield intelligent behavior when combined with knowledge and skills, and then step back to discuss the current AI era, the history of AI (in terms of past eras), and some of what is coming. He will also touch on a selection of both social and ethical issues with respect to AI.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Dr. Paul Rosenbloom is a Professor of Computer Science at USC and Director for Cognitive Architecture Research at USC's Institute for Creative Technologies. His research concentrates on cognitive architecture-“ integrated models of the fixed structures underlying minds-“and on understanding the nature, structure and stature of computing as a scientific domain and its overlap with the other domains of human study. He is a Fellow of the Association for the Advancement of Artificial Intelligence, the Association for the Advancement of Science, and the Cognitive Science Society.
Host: Milind Tambe
Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
-
EE Seminar - Beyond Binary Failures in Networks
Thu, Apr 05, 2018 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Monia Ghobadi, Researcher, Microsoft Research Mobility and Networking
Talk Title: Beyond Binary Failures in Networks
Abstract: Fiber optic cables are the workhorses of today's Internet services, but they are an expensive resource and require significant monetary investment. Their importance has driven a conservative deployment approach with redundancy baked into multiple layers of the network under the assumption that links have a constant reliability status and operate at a fixed capacity. In this talk, I take an unconventional approach and argue that link failures should not be always considered binary events; this approach enables the foundation of a framework for network links with dynamic capacity and reliability. I investigated this idea by conducting the first ever large-scale study of operational optical signals, analyzing over 2,000 channels in a wide-area network for a period of three years, as well as 350,000 links in 20 data center networks worldwide. My analysis uncovered several findings that enable cross-layer optimizations and smart algorithms to improve traffic engineering, increase capacity, and reduce cost. First, the capacity of 99% of wide-area links can be augmented by at least 50 Gbps, leading to an overall capacity gain of more than 100 Tbps. This means we get higher capacity and better availability using the same links. Second, I will show that 99.99% of data center links have an incoming optical power level that is higher than the design threshold; by allowing links to have multiple reliability levels, we can cut the cost of data center networks by nearly half. Finally, the framework opens the door to revisiting several classical networking problems, such as the maximum-flow problem and graph abstractions. Microsoft has invested in this new framework and is rolling out the necessary infrastructure for deployment.
Biography: Monia Ghobadi is a researcher at the Microsoft Research Mobility and Networking research group. Prior to MSR, she was a software engineer at Google. She received her Ph.D. in Computer Science at the University of Toronto and B.Eng. in Computer Engineering at the Sharif University of Technology. Monia is a computer systems researcher with a networking focus and has worked on a broad set of topics, including data center networking, optical networks, transport protocols, network measurement, and hardware-software co-design. Many of the technologies she has helped develop are part of real-world systems at Microsoft and Google. Monia was recognized as an N2women rising star in networking and communications in 2017. Her work has won the best dataset award, Google research excellent paper award (twice), and the ACM IMC best paper award.
Host: Konstantinos Psounis, kpsounis@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Landscape of Practical Blockchain Systems and their Applications
Thu, Apr 05, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Chandrasekaran Mohan, IBM Almaden Research Center
Talk Title: Landscape of Practical Blockchain Systems and their Applications
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The concept of a distributed ledger was invented as the underlying technology of the public or permissionless Bitcoin cryptocurrency network. But the adoption and further adaptation of it for use in the private or permissioned environments is what I consider to be of practical consequence and hence only such private blockchain systems will be the focus of this talk.
Computer companies like IBM, Intel, Oracle, Baidu and Microsoft, and many key players in different vertical industry segments have recognized the applicability of blockchains in environments other than cryptocurrencies. IBM did some pioneering work by architecting and implementing Fabric, and then open sourcing it. Now Fabric is being enhanced via the Hyperledger Consortium as part of The Linux Foundation. A couple of the other efforts include Enterprise Ethereum, Sawtooth and R3 Corda.
While currently there is no standard in the private blockchain space, all the ongoing efforts involve some combination of database, transaction, encryption, virtualization, consensus and other distributed systems technologies. Some of the application areas in which blockchain pilots are being carried out are: smart contracts, derivatives processing, e-governance, Know Your Customer (KYC), healthcare, supply chain management and provenance management.
In this talk, I will describe some use-case scenarios, especially those in production deployment. I will also survey the landscape of private blockchain systems with respect to their architectures in general and their approaches to some specific technical areas. I will also discuss some of the opportunities that exist and the challenges that need to be addressed. Since most of the blockchain efforts are still in a nascent state, the time is right for mainstream database and distributed systems researchers and practitioners to get more deeply involved to focus on the numerous open problems.
An earlier version of this talk was delivered as the opening keynote at the 37th IEEE International Conference on Distributed Computing Systems (ICDCS) in Atlanta (USA) on 6 June 2017. Extensive blockchain related collateral can be found at http://bit.ly/CMbcDB
Biography: Dr. C. Mohan has been an IBM researcher for 36 years in the database and related areas, impacting numerous IBM and non-IBM products, the research and academic communities, and standards, especially with his invention of the ARIES family of database locking and recovery algorithms, and the Presumed Abort distributed commit protocol. This IBM (1997), and ACM and IEEE (2002) Fellow has also served as the IBM India Chief Scientist for 3 years (2006-2009). In addition to receiving the ACM SIGMOD Innovations Award (1996), the VLDB 10 Year Best Paper Award (1999) and numerous IBM awards, Mohan was elected to the US and Indian National Academies of Engineering (2009) and named an IBM Master Inventor (1997). This Distinguished Alumnus of IIT Madras (1977) received his PhD at the University of Texas at Austin (1981). He is an inventor of 50 patents. He is currently focused on Blockchain, Big Data and HTAP technologies (http://bit.ly/CMbcDB, http://bit.ly/CMgMDS). Since 2016, he has been a Distinguished Visiting Professor of China's prestigious Tsinghua University. He has served on the advisory board of IEEE Spectrum, and on numerous conference and journal boards. Mohan is a frequent speaker in North America, Europe and India, and has given talks in 40 countries. He is very active on social media and has a huge network of followers. More information can be found in the Wikipedia page at http://bit.ly/CMwIkP
Host: Prof. Paul Bogdan
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Talyia White
-
EE Seminar - A System Level Approach to the Design of Robust Autonomous Systems
Thu, Apr 05, 2018 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Nikolai Matni, Postdoctoral Scholar, Dept of EECS, UC Berkeley
Talk Title: A System Level Approach to the Design of Robust Autonomous Systems
Abstract: As the systems we build and the environments that they operate in become more complex, first-principle modeling becomes either impossible, impractical, or intractable, motivating the use of machine learning techniques for their control. As impressive as the empirical success of these methods appears to be on stylized test-cases, strong theoretical guarantees of performance, safety, or robustness are few and far between; however, such guarantees are essential when data-driven methods are applied to safety-critical systems or infrastructures. In the first part of this talk, we make concrete steps towards developing performance and stability guarantees in the data-driven setting by considering a classical problem from the optimal control literature, the Linear Quadratic Regulator (LQR), with the added twist that now the system dynamics are unknown. We provide, to the best of our knowledge, the first end-to-end baselines for learning and control in an LQR problem that do not require restrictive or unrealistic assumptions. A key technical tool used in deriving this result is our recently developed System Level Approach (SLA) to Controller Synthesis. The SLA provides a transparent connection between system structure, constraints, and uncertainty and their effects on controller synthesis, implementation, and performance -” we exploit these properties to combine results from contemporary high-dimensional statistics and robust controller synthesis in a way that is amenable to non-asymptotic analysis. We then show how the solution to the "Learning-LQR" problem can be incorporated into an adaptive polynomial-time algorithm that achieves sub-linear regret. In the second part of this talk, we discuss how we can extend these ideas to large-scale data-driven autonomous systems, which encompass future incarnations of the smart-grid, intelligent transportation systems and software-defined networks. In this large-scale distributed setting, an additional challenge must be addressed: even when the system model is exactly known, designing robust systems with optimal performance guarantees is a challenging task. We show how the SLA allows for localized optimal controllers to be synthesized using convex programming, thus extending the performance and robustness guarantees of optimal/robust control, under mild and practically relevant assumptions, to systems of arbitrary size. We illustrate the usefulness of this approach with a frequency regulation problem in the power-grid, and show how it can be used to systematically explore tradeoffs in controller performance, robustness, and synthesis/implementation complexity. We conclude with our vision for a contemporary theory of autonomy and data-driven control, and outline ongoing efforts in extending the previous results to incorporate the guarantees of other learning and control paradigms, such as model predictive control and experiment design.
Biography: Nikolai is a postdoctoral scholar in EECS at UC Berkeley working with Benjamin Recht. Prior to that, he was a postdoctoral scholar in Computing and Mathematical Sciences at the California Institute of Technology. He received the B.A.Sc. and M.A.Sc. in Electrical Engineering from the University of British Columbia, and the Ph.D. in Control and Dynamical Systems from the California Institute of Technology in June 2016 under the advisement of John C. Doyle. His research interests broadly encompass the use of learning, layering, dynamics, control and optimization in the design and analysis of large-scale data-driven cyber-physical systems. He was awarded the IEEE CDC 2013 Best Student Paper Award, the IEEE ACC 2017 Best Student Paper Award (as co-advisor), and was an Everhart Lecture Series speaker at Caltech.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Apr 06, 2018 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Gary Cruz, Director of Academic Affairs & University Relations, Great Minds in STEM
Talk Title: STEM Promotion in Underrepresented Communities and Opportunities for Students
Host: Dr. Prata & EHP
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Su Stevens
-
EE-EP Faculty Candidate, Shimeng Yu, Friday, April 6th at 2pm in EEB 132
Fri, Apr 06, 2018 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Shimeng Yu, Arizona State University
Talk Title: Neuro-Inspired Computing with Resistive Synaptic Devices
Abstract: Resistive device is a two-terminal electronic device based on oxides/chalcogenides that can switch its resistance under programming voltage. This technology has made significant progresses in the past decade as a competitive candidate for the next generation non-volatile memory (NVM), namely resistive random access memory (RRAM). In this presentation, I will discuss its new applications in the context of neuro-inspired computing, as it has a great potential to serve as the synaptic devices in the neuromorphic hardware such as machine/deep learning accelerators. First, I will discuss the desired characteristics of the resistive synaptic devices (e.g. analog multilevel states, weight tuning linearity, variation/noises) and oscillation neuron devices, and show the representative device prototypes of offline training and online training. Next, I will introduce the crossbar array architecture to efficiently implement the weighted sum and weight update operations that are commonly used in the machine/deep learning algorithms, and show the array-level experimental demonstrations for these key operations such as the convolution kernel. Then I will introduce "NeuroSim", a device-circuit-algorithm co-design framework to evaluate the impact of non-ideal device effects on the neuromorphic system performance (i.e. learning accuracy) and trade-offs in the circuit-level performance (i.e. area, latency, energy). Last, I propose to possible future research directions including new materials and device engineering for achieving linear weight update, binarizing neural network algorithm by allowing binary memory cells and our efforts in chip-scale tape-out of a XNOR-Net accelerator with SRAM and heterogeneous integration of RRAM on top of CMOS. This presentation will be concluded with a holistic view of my research vision from materials/device engineering, and circuit/architecture co-optimization for neuro-inspired computing with emerging nanoelectronic devices.
Biography: Shimeng Yu received the B.S. degree in microelectronics from Peking University, Beijing, China in 2009, and the M.S. degree and Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, USA in 2011, and in 2013, respectively. He is currently an assistant professor of electrical engineering and computer engineering at Arizona State University, Tempe, AZ, USA.
His research interests are emerging nano-devices and circuits with a focus on the resistive memories for different applications including machine/deep learning, neuromorphic computing, monolithic 3D integration, hardware security, radiation-hard electronics, etc. He has published >70 journal papers and >100 conference papers with citations >5500 and H-index 34.
Among his honors, he is a recipient of the DOD-DTRA Young Investigator Award in 2015, the NSF Faculty Early CAREER Award in 2016, the ASU Fulton Outstanding Assistant Professor in 2017 and the IEEE Electron Devices Society Early Career Award in 2017.
He served the Technical Program Committee for IEEE International Symposium on Circuits and Systems (ISCAS) 2015-2017, ACM/IEEE Design Automation Conference (DAC) 2017-2018, and IEEE International Electron Devices Meeting (IEDM) 2017-2018, etc.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
-
Astani Civil and Environmental Engineering Seminar
Fri, Apr 06, 2018 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. George Wells, Northwestern University
Talk Title: Biotechnology and Microbial Ecology
Abstract: TBA
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
-
Astani Civil and Environmental Engineering Seminar
Fri, Apr 06, 2018 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. George Wells, Louis Berger Junior Professor of Civil and Environmental Engineering at Northwestern University
Talk Title: The Promise and Peril of DPAOs: Probing Propensity and Mechanisms for Nitrous Oxide Generation by Denitrifying Polyphosphate Accumulating Bacteria
Abstract: See attachment
Host: Dr. Adam Smith
More Information: George Wells Announcement 4-6-2018.pdf
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
-
CS Colloquium: Tim Althoff (Stanford University) – Data Science for Human Well-being
Mon, Apr 09, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Tim Althoff, Stanford University
Talk Title: Data Science for Human Well-being
Series: Computer Science Colloquium
Abstract: The popularity of wearable and mobile devices, including smartphones and smartwatches, has generated an explosion of detailed behavioral data. These massive digital traces provides us with an unparalleled opportunity to realize new types of scientific approaches that provide novel insights about our lives, health, and happiness. However, gaining valuable insights from these data requires new computational approaches that turn observational, scientifically 'weak' data into strong scientific results and can computationally test domain theories at scale.
In this talk, I will describe novel computational methods that leverage digital activity traces at the scale of billions of actions taken by millions of people. These methods combine insights from data mining, social network analysis, and natural language processing to generate actionable insights about our physical and mental well-being. Specifically, I will describe how massive digital activity traces reveal unknown health inequality around the world, and how personalized predictive models can target personalized interventions to combat this inequality. I will demonstrate that modelling how fast we are using search engines enables new types of insights into sleep and cognitive performance. Further, I will describe how natural language processing methods can help improve counseling services for millions of people in crisis.
I will conclude the talk by sketching interesting future directions for computational approaches that leverage digital activity traces to better understand and improve human well-being.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity in RTH 109, seats will be first come first serve.
Biography: Tim Althoff is a Ph.D. candidate in Computer Science in the Infolab at Stanford University, advised by Jure Leskovec. His research advances computational methods to improve human well-being, combining techniques from Data Mining, Social Network Analysis, and Natural Language Processing. Prior to his PhD, Tim obtained M.S. and B.S. degrees from Stanford University and University of Kaiserslautern, Germany. He has received several fellowships and awards including the SAP Stanford Graduate Fellowship, Fulbright scholarship, German Academic Exchange Service scholarship, the German National Merit Foundation scholarship, and a Best Paper Award by the International Medical Informatics Association. Tim's research has been covered internationally by news outlets including BBC, CNN, The Economist, The Wall Street Journal, and The New York Times.
Host: Computer Science Department
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Computer Science Department
-
EE-EP Faculty Candidate, Negar Reiskarimian - Monday, April 9th at 12pm in EEB 132
Mon, Apr 09, 2018 @ 12:00 PM - 01:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Negar Reiskarimian, Columbia University
Talk Title: Breaking Lorentz Reciprocity: From New Physical Concepts to Applications
Abstract: Lorentz reciprocity is a fundamental characteristic of the vast majority of electronic and photonic structures. However, breaking reciprocity enables the realization of non-reciprocal components, such as isolators and circulators, which are critical to electronic and optical communication systems, as well as new components and functionalities based on novel wave propagation modes. In this talk, I will present a novel approach to break Lorentz reciprocity based on linear periodically-time-varying (LPTV) circuits. We have demonstrated the world's first CMOS passive magnetic-free non-reciprocal circulator through spatio-temporal conductivity modulation. Since conductivity in semiconductors can be modulated over a much wider range than the more traditionally exploited permittivity, our structure is able to break reciprocity within a compact form factor with very low loss and high linearity. I will discuss fundamental limits of space-time modulated nonreciprocal structures, as well as new directions to build non-reciprocal components which can ideally be infinitesimal in size. Furthermore, I cover some of the applications of nonreciprocal components in wireless communication systems.
Looking to the future, I am broadly interested in exploring novel fundamental physical concepts that have strong engineering applications. I wish to work in an interdisciplinary area between integrated circuit design and closely related fields such as applied physics, applied electromagnetics and nanophotonics, and to identify and investigate ideas and concepts that can best be implemented using the semiconductor platform. Finally, I will share with you some examples of the exciting research directions I would like to pursue with the aim of participating in building the next generation of technologies that augment human lives.
Biography: Negar Reiskarimian received the Bachelor's and Master's degrees in electrical engineering from Sharif University of Technology in Iran, and is currently a PhD candidate in Electrical Engineering at Columbia University. She has published in top-tier IEEE IC-related journals and conferences, as well as broader-interest high-impact journals in the Nature family. Her research has been widely covered in the press, and featured in IEEE Spectrum, Gizmodo and EE Times among others. She is the recipient of numerous awards and fellowships, including Forbes 30 under 30, Paul Baran Young Scholar, Qualcomm Innovation Fellowship and multiple IEEE societies awards and fellowships.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
-
Biomedical Engineering Seminars
Mon, Apr 09, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Talk Title: TBA
Host: Professor Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
-
Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Apr 09, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Anders Rantzer, Lund University
Talk Title: Towards a Scalable Theory of Control
Series: Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: Classical control theory does not scale well for large systems like traffic networks, power networks and chemical reaction networks. To change this situation, new approaches need to be developed, not only for analysis and synthesis of controllers, but also for modelling and verification. In this lecture we will present a class of networked control problems for which scalable distributed controllers can be proved to achieve the same performance as the best centralized ones. The control objective is stated in terms of frequency weighted H-infinity norms, which makes it possible to combine disturbance rejection at low frequencies with robustness to high frequency measurement noise and model errors. An optimal controller is given in the form of a multi-variable PI controller, which is distributed in the sense that control action along a given network edge is entirely determined by states at nodes connected by that edge. We will discuss some application examples, as well as connections to other aspects of scalability.
Biography: Anders Rantzer received a PhD in 1991 from KTH, Stockholm, Sweden. After postdoctoral positions at KTH and at IMA, University of Minnesota, he joined Lund University in 1993 and was appointed professor of Automatic Control in 1999. During the academic year of 2004-2005 he was visiting associate faculty member at Caltech and 2015-2016 he was Taylor Family Distinguished Visiting Professor at the University of Minnesota. Since 2008 he coordinates the Linnaeus center LCCC at Lund University.
Professor Rantzer is an editorial board member of Proceedings of the IEEE and several other publications. He is a winner of the SIAM Student Paper Competition, the IFAC Congress Young Author Price, and the award for best article in IEE Proceedings - Control Theory and Applications. He is a Fellow of IEEE, a member of the Royal Swedish Academy of Engineering Sciences, and former chairman of the Swedish Scientific Council for Natural and Engineering Sciences.
His research interests are in modeling, analysis and synthesis of control systems, with particular attention to uncertainty, optimization, scalability and adaptation.
Host: Mihailo Jovanovic, mihailo@usc.edu
More Information: rantzer.jpg (JPEG Image, 300 × 400 pixels).pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
-
CS Colloquium: He He (Stanford University) - Learning Interactive Agents
Mon, Apr 09, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: He He, Stanford University
Talk Title: Learning Interactive Agents
Series: CS Colloquium
Abstract: AI has made huge advancement into our daily life and increasingly we require intelligent agents that work intimately with people in a changing environment. However, current systems mostly work in a passive mode: waiting for requests from users and processing them one at a time. An interactive agent must handle real-time, sequential inputs and actively collaborate with people through communication. In this talk, I will present my recent work addressing challenges in real-time language processing and collaborative dialogue. The first part involves making predictions with incremental inputs. I will focus on the application of simultaneous machine interpretation and show how we can produce both accurate and prompt translations. Then, I will present my work on building agents that collaborate with people through goal-oriented conversation. I will conclude by discussing future directions towards adaptive, active agents.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: He He is a postdoctoral researcher at Stanford University. She earned her Ph.D. in Computer Science at the University of Maryland, College Park. She is interested in natural language processing and machine learning. Her research focuses on building intelligent agents that work in a changing environment and interact with people, with an emphasis on language-related problems. Specific applications include dependency parsing, simultaneous machine interpretation, and goal-oriented dialogue. She is the recipient of the 2016 Larry S. Davis doctoral dissertation award.
Host: Fei Sha
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
CS Colloquium: Neha Kumar (Georgia Institute of Technology) - Solidarity Through Design: Across Borders and Intersections
Tue, Apr 10, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Neha Kumar, Georgia Institute of Technology
Talk Title: Solidarity Through Design: Across Borders and Intersections
Series: CS Colloquium
Abstract: The field of human-computer interaction is increasingly engaging in technology design targeting underserved contexts, both across and beyond the global south. Populations in these parts may be socioeconomically disadvantaged, impacted by patriarchy, infrastructurally challenged, discriminated on account of caste or class, or all of the above. Dominant discourse considers access to mobile technologies a key asset for addressing these multiple forms of marginalization. However, there may be other assets as well---such as the presence of care, extensive social ties, or resilient sensibilities---that my work examines and leverages.
In my talk, I will present research conducted in three key areas of global development---access, health, and education---to discuss how we might engage in culturally relevant and appropriate technology design for populations across borders and intersections. Taking place in similar but different contexts across India, Cuba, and the United States, these projects highlight how lessons from one context might inform design in another.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Neha Kumar is an assistant professor at the Georgia Institute of Technology. Her research lies at the intersection of human-centered computing and global development. She received her Ph.D. from the School of Information at UC Berkeley in 2013. Before starting at Georgia Tech in 2015, she completed two postdoctoral assignments---the first at University of Washington's Computer Science and Engineering department and the second at the University of Southern California's Annenberg School of Communication. She also holds two Master's degrees from Stanford University---in Computer Science and Learning, Design and Technology. Neha's research publications have received multiple awards at major conferences. She is an inaugural member of the ACM Future of Computing Academy. She received the Lockheed Inspirational Young Faculty award from Georgia Tech's College of Computing in 2017. She was also a recipient of Google's Anita Borg Scholarship and a Facebook Fellowships Finalist in 2012.
Host: Bistra Dilkina
Location: 100D
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
EE Seminar: Analysis, Design, and Operation of Secure Cyber-Physical Systems
Tue, Apr 10, 2018 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Fabio Pasqualetti, Assistant Professor, University of California, Riverside
Talk Title: Analysis, Design, and Operation of Secure Cyber-Physical Systems
Abstract: Today's cyber-physical systems are the building blocks of smart and citizen-centric applications that will revolutionize the way people interact with the urban environment. Smart systems, cities, and communities will emerge, in which advanced levels of autonomy hold the promise of greater efficiency, reliability and sustainability in areas of national interest and social need, such as health, energy, and transportation. In this new realm of applications, however, enhanced connectivity and advanced autonomy will also pose novel and significant risks to people and the infrastructure, including safety, security, and privacy.
In this talk, I present a unified framework for the analysis of fundamental vulnerabilities affecting cyber-physical systems, the design of targeted detection and protection schemes, and the construction of systems that are provably resilient to accidental malfunctions and malicious attacks. I show how cyber-physical security differs from well-established disciplines, including cyber security and fault tolerance, and how our control- and graph-theoretic methods complement existing security practices to fully protect cyber-physical systems. Further, I reveal a novel class of integrity attacks against smart power grids, and show how these attacks lead to the formulation of novel sparse network control problems, which we also solve. Finally, I discuss directions of future research and open questions in cyber-physical security.
Biography: Fabio Pasqualetti is an Assistant Professor in the Department of Mechanical Engineering, University of California, Riverside. He completed a Doctor of Philosophy degree in Mechanical Engineering at the University of California, Santa Barbara, in 2012, a Laurea Magistrale degree (M.Sc. equivalent) in Automation Engineering at the University of Pisa, Italy, in 2007, and a Laurea degree (B.Sc. equivalent) in Computer Engineering at the University of Pisa, Italy, in 2004. He received a Young Investigator Program award from ARO in 2017, and the 2016 TCNS Outstanding Paper Award from IEEE CSS. His main research interest is in secure control systems, with application to multi-agent networks, distributed computing, and power networks. Other interests include computational neuroscience, vehicle routing, and combinatorial optimization.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Epstein Institute Seminar, ISE 651
Tue, Apr 10, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Shiyu Zhou, Professor, University of Wisconsin-Madison
Talk Title: Nonparametric Modeling and Prognosis of Condition Monitoring Signals for Internet of Things (IoT) Enabled Systems
Host: Dr. Qiang Huang
More Information: April 10, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
Research and Technology Seminar
Wed, Apr 11, 2018 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sunil Bharitkar, Distinguished Member of Tech. Staff (HP Labs)
Talk Title: Advances in Joint Signal Processing, Perception, and Machine Learning at HP Labs
Abstract: In HP's Emerging Compute Lab, research is being conducted at the intersection of signal processing, auditory perception and machine learning to create fundamentally new experiences for differentiation in HP devices including VR HMD. In this talk we will present various techniques and algorithms, incorporating knowledge of binaural perception, machine learning, and signal processing, to enhance low-frequency perception, spatial rendering, and automated content classification. The research results have been validated through perceptual testing in large-scale studies giving statistically meaningful results. Ongoing research being conducted in the areas deep learning (stacked autoencoders and LSTM) for VR head-related transfer function synthesis, content classification, speech and multimodal biometrics, sensing towards emotion interpretation, and cancer cell data classification (jointly with Life Sciences Lab) will also be presented. The presentation will be accompanied with demonstrations.
Biography: Sunil Bharitkar received his Ph.D. in Electrical Engineering from the University of Southern California (USC) in 2004 and is involved in research in speech/audio analysis and processing including spatial audio for AR/VR, biometric & biomedical signal processing, multimodal signal processing, and machine learning. From 2011-2016 he was at Dolby leading/guiding research in audio, signal processing, haptics, machine learning, hearing augmentation, and standardization activities at ITU, SMPTE, AES. He co-founded the company Audyssey Laboratories in 2002 where he was VP of Research and responsible for inventing new technologies which were licensed to companies including IMAX, Denon, Audi, Sharp, etc. He also taught in the Department of Electrical Engineering at USC. Sunil has published over 50 technical papers and has over 20 patents in the area of signal processing applied to acoustics, neural networks and pattern recognition, and a textbook (Immersive Audio Signal Processing) from Springer-Verlag. He is a reviewer for papers at various conferences and journals. He has also been on the Organizing and Technical Program Committees of various conferences such as the 2008 and 2009 European Sig. Proc. Conference (EUSIPCO), the 57th AES Conference, SMPTE Conferences. He has also served as an invited tutorial speaker at the 2006 IEEE Conf. on Acoustics Speech and Signal Processing (ICASSP). He is a Senior Member of the IEEE, the Acoustical Soc. of America (ASA), European Association for Signal and Image Processing (EURASIP), and the Audio Eng. Soc. (AES). Sunil is a PADI diver and enjoys playing the Didgeridoo.
Host: Panos Georgiou and Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
-
CiSoft Seminar
Wed, Apr 11, 2018 @ 12:00 PM - 01:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Mr. Jim Crompton, Reflections Data Consulting Founder
Talk Title: Is there an Autonomous Well in Your Future
Series: CiSoft Seminar
Host: CiSoft
Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Please RSVP: legat@usc.edu
Contact: Juli Legat
-
From Gaussian Multiterminal Source Coding to Distributed Karhunen Loève Transform
Wed, Apr 11, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jun Chen, Department of Electrical and Computer Engineering, McMaster University
Talk Title: From Gaussian Multiterminal Source Coding to Distributed Karhunen Loève Transform
Series: Joint Seminar Series Seminar Series on Cyber-Physical Systems and CommNetS-MHI Seminar Series
Abstract: Characterizing the rate-distortion region of Gaussian multiterminal source coding is a longstanding open problem in network information theory. In this talk, I will show how to obtain new conclusive results for this problem using nonlinear analysis and convex relaxation techniques. A byproduct of this line of research is an efficient algorithm for determining the optimal distributed Karhunen-“Loève transform in the high-resolution regime, which partially settles a question posed by Gastpar, Dragotti, and Vetterli. I will also introduce a generalized version of the Gaussian multiterminal source coding problem where the source-encoder connections can be arbitrary. It will be demonstrated that probabilistic graphical models offer an ideal mathematical language for describing how the performance limit of a generalized Gaussian multiterminal source coding system depends on its topology, and more generally they can serve as the long-sought platform for systematically integrating the existing achievability schemes and converse arguments. The architectural implication of our work for low-latency lossy source coding will also be discussed. This talk is based on joint work with Jia Wang, Farrokh Etezadi, and Ashish Khisti.
Biography: Jun Chen received the B.E. degree with honors in communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2001 and the M.S. and Ph.D. degrees in electrical and computer engineering from Cornell University, Ithaca, NY, in 2004 and 2006, respectively. He was a Postdoctoral Research Associate in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, Urbana, IL, from September 2005 to July 2006, and a Postdoctoral Fellow at the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, from July 2006 to August 2007. Since September 2007 he has been with the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada, where he is currently an Associate Professor and a Joseph Ip Distinguished Engineering Fellow. His research interests include information theory, machine learning, wireless communications, and signal processing. He received the Josef Raviv Memorial Postdoctoral Fellowship in 2006, the Early Researcher Award from the Province of Ontario in 2010, and the IBM Faculty Award in 2010. He served as an Associate Editor for the IEEE Transactions on Information Theory from 2014 to 2016.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
-
John Laufer Lecture
Wed, Apr 11, 2018 @ 03:00 PM - 04:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Charles Meneveau, Louis M. Sardella Professor of Mechanical Engineering, Johns Hopkins University
Talk Title: New Analytical Models for Turbulence Spectra and Turbine Wakes in Wind Farms
Abstract: Reduced order, analytically tractable models remain an important tool in the wind energy area, both for design and control purposes. In this presentation we focus on two fluid mechanical themes relevant to wind farm design and control. The first topic deals with spectral characteristics of the fluctuations in power generated by an array of wind turbines in a wind farm. We show that modeling of the spatio-temporal structure of canonical turbulent boundary layers coupled with variants of the Kraichnan's random sweeping hypothesis can be used to develop analytical predictions of the frequency spectrum of power fluctuations of wind farms. In the second part we describe a simple (deterministic) dynamic wake model, its use for wind farm control, and its extension to the case of yawed wind turbines. The work to be presented arose from collaborations with Juliaan Bossuyt, Johan Meyers, Richard Stevens, Michael Wilczek, Laura Lukasen, Michael Howland, Carl Shapiro and Dennice Gayme. We are grateful for National Science Foundation support.
Biography: Charles Meneveau is the Louis M. Sardella Professor in the Department of Mechanical Engineering at Johns Hopkins University and is Associate Director of the Institute for Data Intensive Engineering and Science (IDIES) at Hopkins. He received his B.S. degree in Mechanical Engineering from the Universidad Técnica Federico Santa MarÃa in ValparaÃso, Chile, in 1985 and M.S, M.Phil. and Ph.D. degrees from Yale University in 1987, 1988 and 1989, respectively. During 1989/90 he was a postdoctoral fellow at the Center for Turbulence Research at Stanford. He has been on the Johns Hopkins faculty since 1990. His area of research is focused on understanding and modeling hydrodynamic turbulence, and complexity in fluid mechanics in general. The insights that have emerged from Professor Meneveau's work have led to new numerical models for Large Eddy Simulations (LES) and applications in engineering and environmental flows, including wind farms. He also focuses on developing methods to share the very large data sets that arise in computational fluid dynamics. He is Deputy Editor of the Journal of Fluid Mechanics and served (until 2015) for 13 years as the Editor-in-Chief of the Journal of Turbulence. Professor Meneveau is a member of the US National Academy of Engineering (2018), a foreign corresponding member of the Chilean Academy of Sciences (2005), and a Fellow of the American Academy of Mechanics, the U.S. American Physical Society and the American Society of Mechanical Engineers. He received an honorary doctorate from the Danish Technical University (in 2016), the inaugural Stanley Corrsin Award from the American Physical Society (2011), the Johns Hopkins University Alumni Association's Excellence in Teaching Award (2003), and the APS' François N. Frenkiel Award for Fluid Mechanics (2001).
Host: Department of Aerospace and Mechanical Engineering
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
-
CAIS Seminar: Dr. Edward Kaplan (Yale) – Adventures in Policy Modeling!
Wed, Apr 11, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Edward Kaplan, Yale
Talk Title: Adventures in Policy Modeling!
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Policy Modeling refers to the application of operations research, statistics, and other quantitative methods to model policy problems. Recognizing that analyses of all sorts often exhibit diminishing returns in insight to effort, the hope is to capture key features of various policy issues with relatively simple 'first-strike' models. Problem selection and formulation thus compete with the mathematics of solution methods in determining successful applications: where do good problems come from? How can analysts tell if a particular issue is worth pursuing? In addressing these questions, Dr. Kaplan will review some personal adventures in policy modeling selected from public housing, HIV/AIDS prevention, bioterror preparedness, suicide bombings and counterterrorism, in vitro fertilization, predicting presidential elections, and sports.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Dr. Edward H. Kaplan is the William N. and Marie A. Beach Professor of Operations Research, Public Health, and Engineering at Yale. An elected member of both the National Academies of Engineering and Medicine, his research in HIV prevention and counterterrorism has been recognized with the Lanchester Prize, the Edelman Award, and numerous other awards in operations research and public health. Dr. Kaplan was the President of the Institute for Operations Research and the Management Sciences (INFORMS) during 2016, where he preferred the title 'Member in Chief.'
Host: Milind Tambe
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Computer Science Department
-
CiSoft Seminar
Wed, Apr 11, 2018 @ 11:00 PM - 01:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Mr. Jim Crompton, Reflections Data Consulting Founder
Talk Title: Is there an Autonomous Well in Your Future
Series: CiSoft Seminar
Host: CiSoft
Location: 306
Audiences: Please RSVP: legat@usc.edu
Contact: Juli Legat
-
CS Colloquium: Mikael Henaff (New York University) - Learning Models of the Environment for Sample-Efficient Planning
Thu, Apr 12, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Mikael Henaff, New York University
Talk Title: Learning Models of the Environment for Sample-Efficient Planning
Series: CS Colloquium
Abstract: Learning to predict how an environment will evolve and the consequences of one's actions is an important ability for autonomous agents, and can enable planning with relatively few interactions with the environment which may be slow or costly. However, learning an accurate predictive model is made difficult due to several challenges, such as partial observability, long-term dependencies and inherent uncertainty in the environment. In this talk, I will present my work on architectures designed to address some of these challenges, as well as work focused on better understanding recurrent network memory over long timescales. I will then present some recent work applying learned environment models for planning, using a simple gradient-based approach which can be used in both discrete and continuous action spaces. This approach is able to match or outperform model-free methods while requiring fewer environment interactions and still enabling real-time performance.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Mikael Henaff is a fifth-year PhD student in computer science at New York University, advised by Yann LeCun. His current research interests are centered around learning predictive models of the environment, model-based reinforcement learning and memory-augmented neural networks. Prior to his Ph.D studies, he worked at the NYU Langone Medical Center and has interned several times at Facebook AI Research. He holds a B.S in mathematics from the University of Texas at Austin and an M.S in mathematics from New York University.
Host: Fei Sha
Location: Olin Hall of Engineering (OHE) - 100D
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
EE Seminar: Towards Generalizable Imitation in Robotics
Thu, Apr 12, 2018 @ 01:30 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Animesh Garg, Postdoctoral Researcher, Stanford University AI lab
Talk Title: Towards Generalizable Imitation in Robotics
Abstract: Robotics and AI are experiencing radical growth, fueled by innovations in data-driven learning paradigms coupled with novel device design, in applications such as healthcare, manufacturing and service robotics. And in our quest for general purpose autonomy, we need abstractions and algorithms for efficient generalization.
Data-driven methods such as reinforcement learning circumvent hand-tuned feature engineering, albeit lack guarantees and often incur a massive computational expense: training these models frequently takes weeks in addition to months of task-specific data-collection on physical systems. Further such ab initio methods often do not scale to complex sequential tasks. In contrast, biological agents can often learn faster not only through self-supervision but also through imitation. My research aims to bridge this gap and enable generalizable imitation for robot autonomy. We need to build systems that can capture semantic task structures that promote sample efficiency and can generalize to new task instances across visual, dynamical or semantic variations. And this involves designing algorithms that unify in reinforcement learning, control theoretic planning, semantic scene & video understanding, and design.
In this talk, I will discuss two aspects of Generalizable Imitation: Task Imitation, and Generalization in both Visual and Kinematic spaces. First, I will describe how we can move away from hand-designed finite state machines by unsupervised structure learning for complex multi-step sequential tasks. Then I will discuss techniques for robust policy learning to handle generalization across unseen dynamics. I will revisit structure learning for task-level understanding for generalization to visual semantics.
And lastly, I will present a program synthesis based method for generalization across task semantics with a single example with unseen task structure, topology or length. The algorithms and techniques introduced are applicable across domains in robotics; in this talk, I will exemplify these ideas through my work on medical and personal robotics.
Biography: Animesh is a Postdoctoral Researcher at Stanford University AI lab. Animesh is interested in problems at the intersection of optimization, machine learning, and design. He studies the interaction of data-driven Learning for autonomy and Design for automation for human skill-augmentation and decision support. Animesh received his Ph.D. from the University of California, Berkeley where he was a part of the Berkeley AI Research center and the Automation Science Lab. His research has been recognized with Best Applications Paper Award at IEEE CASE, Best Video at Hamlyn Symposium on Surgical Robotics, and Best Paper Nomination at IEEE ICRA 2015. And his work has also featured in press outlets such as New York Times, UC Health, UC CITRIS News, and BBC Click.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Epstein Department Seminar
Thu, Apr 12, 2018 @ 02:00 PM - 03:30 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Michael Yu Wang, Profesor, Hong Kong University of Science and Technology
Talk Title: Architectured Meso-Scale Cellular Materials and Structures: Topology Optimization for Additive Manufacturing
Host: Dr. Yong Chen
More Information: Michael Yu Wang_flyer.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
2018 Viterbi Keynote Lecture
Thu, Apr 12, 2018 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: David Tse, Thomas Kailath and Guanghan Xu Professor, Stanford University
Talk Title: Maximum likelihood Genome Sequencing
Series: Viterbi Lecture
Abstract: Genome sequencing is one of the biggest breakthroughs in science in the past two decades. Modern sequencing methods use linking data at multiple scales to reconstruct pertinent information about the genome. Many such reconstruction problems can be formulated as maximum likelihood sequence decoding from noisy linking data. We discuss two in this talk: haplotype phasing, the problem of sequencing genomic variations on each of the maternal and paternal chromosomes, and genome scaffolding, the problem of finishing genome assembly using long-range 3D contact data. While maximum likelihood sequence decoding is NP-hard in both of these problems, spectral and linear programming relaxations yield efficient approximation algorithms that can provably achieve the information theoretic limits and perform well on real data. These results parallel the biggest success of information theory: efficiently achieving the fundamental limits of communication.
Biography: David Tse received the B.A.Sc. degree in systems design engineering from University of Waterloo in 1989, and the M.S. and Ph.D. degrees in electrical engineering from Massachusetts Institute of Technology in 1991 and 1994 respectively. From 1995 to 2014, he was on the faculty of the University of California at Berkeley. He received the Claude E. Shannon Award in 2017 and was elected member of the U.S. National Academy of Engineering in 2018. Previously, he received a NSF CAREER award in 1998, the Erlang Prize from the INFORMS Applied Probability Society in 2000 and the Frederick Emmons Terman Award from the American Society for Engineering Education in 2009. He received multiple best paper awards, and is the inventor of the proportional-fair scheduling algorithm used in all third and fourth-generation cellular systems.
Host: Sandeep Gupta, sandeep@usc.edu
More Info: https://minghsiehee.usc.edu/viterbi-lecture/
Webcast: https://bluejeans.com/401381224/More Information: 20180412 Tse Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://bluejeans.com/401381224/
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
Event Link: https://minghsiehee.usc.edu/viterbi-lecture/
-
W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Apr 13, 2018 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Joseph Greenfield, Associate Professor of Information Technology Practice at USC, Digital Forensics Consultant at Maryman & Associates
Talk Title: Current Threats in Cybersecurity
Host: Dr. Prata & EHP
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Su Stevens
-
Munushian Keynote Speaker - Dr. William Phillips - Nobel Laureate, Physics 1997, Friday, April 13th at 2pm in GER 124 Auditorium
Fri, Apr 13, 2018 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. William Phillips, Joint Quantum Institute, National Institute of Standards and Technology and University of Maryland
Talk Title: Quantum Information: a scientific and technological revolution for the 21st century
Abstract: Two of the great scientific and technical revolutions of the 20th century were the discovery of the quantum nature of the submicroscopic world, and the advent of information science and engineering. Both of these have had a profound effect not only on our daily lives but on our worldview. Now, at the beginning
of the 21st century, we see a marriage of quantum mechanics and information science in a new revolution: quantum information. Quantum computation and quantum communication are two aspects of this revolution.
The first is highly speculative: a new paradigm more different from today's digital computers than those computers are from the ancient abacus. The second is already a reality, providing information transmission whose security is guaranteed by the laws of physics. The JQI/NIST Laser Cooling and Trapping Group is studying the use of single, ultracold atoms as quantum bits, or qubits, for quantum information processing.
Biography: William D. Phillips was born in 1948, in Wilkes-Barre PA, and attended public primary and secondary schools in Pennsylvania. He received a B.S. in
Physics from Juniata College in 1970 and a Ph.D. from MIT in 1976. After two years as a Chaim Weizmann postdoctoral fellow at MIT, he joined the staff of the
National Institute of Standards and Technology (then the National Bureau of Standards) in 1978. He is currently leader of the Laser Cooling and Trapping Group in the Quantum Measurement Division of NIST's Physical Measurement Laboratory, and a Distinguished University Professor at the University of Maryland. He is a Fellow of the Joint Quantum Institute, a cooperative research organization of NIST and the University of Maryland that is devoted to the study of quantum coherent phenomena. At the JQI he is the co-director of an NSF-funded Physics Frontier Center focusing on quantum phenomena that span different subfields of physics.
The research group led by Dr. Phillips at NIST has been responsible for developing some of the main techniques now used for laser-cooling and cold-atom experiments in laboratories around the world, including the deceleration of atomic beams, magnetic trapping of atoms, the storage and manipulation of cold atoms with optical lattices, and the coherent manipulation of Bose-Einstein condensates. In 1988 the NIST group discovered that laser cooling could reach temperatures much lower than had been predicted by theory, a result that led to a new understanding of laser cooling and contributed to many of the subsequent developments in cold atomic gases. Early achievements included reaching laser-cooling temperatures within a millionth of a degree of Absolute Zero. Today, the group pursues research in laser cooling and trapping; Bose-Einstein condensation; atom optics; collisions of cold atoms; quantum information processing; cold atoms in optical lattices; production and transmission of non-classical light; and the study of cold-atom analogs to condensed matter systems. Phillips and colleagues demonstrated the first "atomic fountain" clock as proposed by Zacharias. Such clocks, as realized in other laboratories, have become the primary time standards for world timekeeping.
Dr. Phillips is a fellow of the American Physical Society and the American Academy of Arts and Sciences. He is a Fellow and Honorary Member of the Optical Society of America, a member of the National Academy of Sciences and the Pontifical Academy of Sciences, and a corresponding member of the Mexican Academy of Sciences. He is the recipient of the Gold Medal of the U. S. Department of Commerce (1993), the Michelson Medal of the Franklin Institute (1996), the Schawlow Prize of the American Physical Society (1998), and the Service to America Medal, Career Achievement Award 2006. In 1997, Dr. Phillips shared the Nobel Prize in Physics "for development of methods to cool and trap atoms with laser light."
Host: EE-Electrophysics
More Info: minghsiehee.usc.edu/about/lectures
Location: Ethel Percy Andrus Gerontology Center (GER) - 124
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: minghsiehee.usc.edu/about/lectures
-
Astani Civil and Environmental Engineering Seminar
Fri, Apr 13, 2018 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. John Seinfeld, California Institute of Technology
Talk Title: Aerosols and Climate
Abstract: See attachment
More Information: John Seinfeld seminar announcement.pdf
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
-
NL Seminar- Finding memory in time
Fri, Apr 13, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Yuanhang Su , USC
Talk Title: Finding memory in time
Series: Natural Language Seminar
Abstract: For a large number of natural language processing NLP problems, we are concerned with finding semantic patterns from input sequences. In recurrent neural network RNN based approach, such pattern is encoded in a vector called hidden state. Since Elmans Finding structure in time published in 1990, it has long been believed that the magic power of RNNs memory, which is enclosed inside the hidden state, can handle very long sequences. Yet besides some experimental observations, there is no formal definition of RNNs memory, let alone a rigid mathematical analysis of how RNNs memory forms.
This talk will focus on understanding memory from two viewpoints. The first viewpoint is that memory is a function that maps certain elements in the input sequences to the current output. Such definition, for the first time in literature, allows us to do detailed analysis of the memory of simple RNN SRN, long short term memory ELSTM, and gated recurrent unit GRU. It also opens the door for further improving the existing RNN basic models. The end results are the proposal of a new basic RNN model called extended LSTM ELSTM with outstanding performance for complex language tasks, and a new macro RNN model called dependent bidirectional RNN DBRNN with smaller cross entropy than bidirectional RNN BRNN and encoderdecoder enc dec models. The second viewpoint is that memory is a compact representation of sparse sequential data. From this perspective, the process of generating hidden state of RNN is simply dimension reduction. Thus, method like principal component analysis PCA which does not require labels for training becomes attractive. However, there are two known problems in implementing PCA for NLP problems: the first is computational complexity; the second is vectorization of sentence data for PCA. To deal with this problem, an efficient dimension reduction algorithm called tree structured multi linear PCA is proposed.
Biography: Yuanhang Su received the dual B.S. degree in Electrical Engineering and Automation and Electronic and Electrical Engineering from University of Strathclyde, Glasgow, U.K. and Shanghai University of Electric Power, Shanghai, China, respectively in 2009, and the M.S. degree in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 2010. From 2011 to 2015, he worked as image video camera software and algorithm engineer for a Los Angeles startup named Exaimage, Shanghai Aerospace Electronics Technology Institute in China and Huawei Technology in China consecutively. He joined MCL lab in 2016 spring, and is currently pursing his Ph.D. in computer vision, natural language processing and machine learning.
Host: Nanyun Peng
More Info: http://nlg.isi.edu/nl-seminar/
Location: 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
-
CS Colloquium: Srivatsan Ravi (ISI USC) - Synchronization using Transactions: Lower bounds and Algorithms
Mon, Apr 16, 2018 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Srivatsan Ravi, ISI USC
Talk Title: Synchronization using Transactions: Lower bounds and Algorithms
Series: CS Colloquium
Abstract: Designing algorithms to exploit today's distributed computing platforms ranging
from general-purpose multicore CPUs, cloud infrastructures to domain-specific decentralized computing systems emphasizes the need for designing robust and fault-tolerant synchronization protocols. However, traditional techniques for synchronization are either too coarse-grained to exploit concurrency or require application-specific fine-grained synchronization.
The Transactional Memory (TM) abstraction is a synchronization mechanism
for multicore programming proposed as a middle ground: it intends to combine an easy-to-use programming model with an efficient utilization of hardware concurrency. TM allows the programmer to speculatively execute sequences of shared-memory operations as atomic in-memory transactions with safe semantics: state witnessed by each transaction is consistent with some sequential execution. Thus, the programmer can design applications having largely sequential semantics in mind and let TM take care, at run-time, of dealing with problems associated with process asynchrony and adversarial failures.
In this talk, we focus on a model for hybrid TMs that exploits hardware extensions in prevalent CPU architectures to support small transactions. We present lower bound proof constructions for implementing safe hybrid transactions and its implications for the complexity of concurrent data structures. We conclude by outlining how transactions as a synchronization mechanism can serve as highly robust universal constructions for domain-specific distributed computing models.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity, seats will be first come first serve.
Biography: Srivatsan Ravi is a computer scientist at the Information Sciences Institute in University of Southern California (USC). His research interests are centered around the theory and practice of distributed computing. Specifically, he works on algorithms and lower bounds for fault-tolerant distributed systems. His research is motivated by emerging new hardware trends that require a new abstract computation model or via introduction of distributed computing techniques to domains where the sequential implementation continues to be state-of-the-art.
He received his Ph.D. degree from Technical University of Berlin in Germany, where he received the Marie Curie Ph.D. Fellowship and was a member of Deutsche-Telekom Labs, Berlin. His Masters degree is from Cornell University, U.S.A and his Bachelors degree is from Anna University, India.
Host: John Heidemann
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
Biomedical Engineering Seminars
Mon, Apr 16, 2018 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Talk Title: TBA
Host: Professor Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
-
Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Apr 16, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: John Baras, The Institute for Systems Research, University of Maryland
Talk Title: Networked Cyber-Physical Systems (Net-CPS)
Series: Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: We describe recent results on foundational aspects of modeling, architecture and performance of networked cyber-physical systems. These include: multi-layer multigraph models, constrained coalitional games, analysis of trust and mistrust in collaboration, dynamics of signed graphs, distributed consensus with adversaries, new concepts of value of information and event-driven inference and decision making, non-commutative probability models. We conclude with directions for future research.
Biography: John Baras is with the University of Maryland College Park, where he holds he endowed Lockheed Martin Chair in Systems Engineering. He received the Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens, Greece, 1970; the M.S. and Ph.D. degrees in Applied Mathematics from Harvard University 1971, 1973. Since 1973, he has been a faculty member in the Electrical and Computer Engineering Department, and in the Applied Mathematics, Statistics and Scientific Computation Program, at the University of Maryland College Park. Founding Director of the Institute for Systems Research (ISR), 1985 to 1991. Since 1992, Founding Director of the Maryland Center for Hybrid Networks (HYNET). Since 2013, Guest Professor at the Royal Institute of Technology (KTH), Sweden. IEEE Life Fellow, SIAM Fellow, AAAS Fellow, NAI Fellow, IFAC Fellow, AIAA Associate Fellow, and a Foreign Member of the Royal Swedish Academy of Engineering Sciences (IVA). Received the 1980 George Axelby Award from the IEEE Control Systems Society, the 2006 Leonard Abraham Prize from the IEEE Communications Society, the 2014 Tage Erlander Guest Professorship from the Swedish Research Council, and a three year (2014-2017) Senior Hans Fischer Fellowship from the Institute for Advanced Study of the Technical University of Munich, Germany. He was inducted in the A. J. Clark School of Engineering Innovation Hall of Fame (2016) of the University of Maryland and was awarded the 2017 IEEE Simon Ramo Medal, and the 2017 AACC Richard E. Bellman Control Heritage Award. His research interests include systems and control, optimization, communication networks, signal processing and understanding, robotics, computing systems, network security and trust, systems biology, healthcare management systems, model-based systems engineering.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
-
EE Seminar - Controlling Dynamic Ensembles: from Cells to Societies
Tue, Apr 17, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jr-Shin Li, Das Family Distinguished Career Development Associate Professor of Systems Science and Mathematics, Washington University in St. Louis
Talk Title: Controlling Dynamic Ensembles: from Cells to Societies
Abstract: Natural and engineered systems that consist of populations of isolated or interacting dynamical components exhibit levels of complexity that are beyond human comprehension. These complex systems often require an appropriate excitation, an optimal hierarchical organization, or a periodic dynamical structure, such as synchrony, to function as desired or operate optimally. In many applications, the dynamics of such ensemble systems can only be regulated by the use of a single or sparsely distributed external inputs in order to alter their state configurations or dynamic patterns; for example, excitation of a large quantum ensemble using a sequence of electromagnetic fields in nuclear magnetic resonance spectroscopy and imaging, entrainment of a population of circadian cells by a light protocol in chronobiology, and desynchronization of a pathologically synchronized neuron ensemble with neurostimulation for the treatment of neurological disorders, such as Parkinson's disease or epilepsy, in brain medicine. This unconventional control paradigm gives rise to challenging problems regarding robust broadcast control and computation for underactuated dynamic populations. Moreover, valid and precise mathematical models for describing the dynamics of such complex systems are often elusive, while their measurement data are available. This talk will address theoretical and computational challenges for targeted coordination of both isolated and networked ensemble systems arising in diverse areas at different scales. Both data-driven and model-based approaches for learning, decoding, control, and computation of dynamic structures and patterns in ensemble systems will be presented. Practical control designs, including synchronization waveforms for pattern formation in nonlinear oscillatory networks and optimal pulses in quantum control will be illustrated along with their experimental realizations. Lastly, future directions and opportunities in Systems and Controls will be discussed.
Biography: Dr. Jr-Shin Li is currently Das Family Distinguished Career Development Associate Professor of Systems Science and Mathematics in the Department of Electrical and Systems Engineering at Washington University in St. Louis, where he also holds a joint appointment in the Division of Biology & Biomedical Sciences since he joined Washington University in 2006. Dr. Li received a B.S. and an M.S. from National Taiwan University, and a Ph.D. in Applied Mathematics from Harvard University in 2006. His research interests lie in the areas of systems, computational, and data sciences, and their applications to biology, neuroscience, quantum physics, brain medicine, and public health. He is a recipient of the NSF Career Award in 2008 and the AFOSR Young Investigator Award in 2010. He is currently Associate Editor of the SIAM Journal on Control and Optimization (SICON) and the IEEE Transactions on Control Systems Technology (TCST).
Host: Edmond Jonckheere, jonckhee@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Epstein Institute Seminar, ISE 651
Tue, Apr 17, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Shabbir Ahmed, Chaired Professor, Georgia Tech
Talk Title: Decentralized Generation Scheduling in Energy Networks
Host: Prof. Suvrajeet Sen
More Information: April 17, 2018.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
EE Seminar - From DC to Daylight: Harnessing Electromagnetic Fields for Bioelectronics, Wireless Communications, and Silicon Photonics
Wed, Apr 18, 2018 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Constantine Sideris, Postdoctoral Scholar, Caltech
Talk Title: From DC to Daylight: Harnessing Electromagnetic Fields for Bioelectronics, Wireless Communications, and Silicon Photonics
Abstract: Maxwell's equations are responsible for explaining the fundamental operating principles behind most of today's technology. In this talk, we will explore how understanding and controlling electromagnetic fields can lead to significant impact across a multitude of applications over a wide frequency range on the electromagnetic spectrum. Starting from the low-frequency end of the spectrum, I will present the design and implementation of a new integrated magnetic biosensor. The magnetic biosensor is fabricated in a standard CMOS foundry process without any post-fabrication processing and can perform in-vitro detection of DNA, proteins, and cells by utilizing magnetic nanoparticles as labels. We will discuss three different, improved sensor designs, which address sensor gain uniformity, enable multiplex target detection, and compensate sensor electrical and thermal drift based on spatial and temporal manipulations of the magnetic fields. I will present initial in-vitro biodetection experiments, and discuss future research directions moving towards in-vivo sensing with wearable and implantable devices, as well as actuation via targeted therapeutics. Next, we will look into the RF domain and develop maximal performance bounds for antennas. I will present a rapid simulation technique which, when coupled with heuristic optimization algorithms, can quickly and effectively produce new antenna structures de-novo with little or no manual intervention. The efficacy of these techniques will be shown in the context of a 3D printed coupling antenna for a dielectric waveguide communication link. Moving higher in frequency, we will explore the near-infrared (NIR) part of the spectrum in the context of silicon photonic device optimization. I will present on-going work in designing grating coupler and power splitting devices with arbitrary splitting ratios by using adjoint optimization and highly efficient integral equation techniques. We will also explore exciting future directions in these research areas, leveraging modern computation and efficient numerical algorithms as well as holistic co-design of circuits and electromagnetics.
Biography: Constantine Sideris received the B.S., M.S., and PhD degrees with honors from the California Institute of Technology in 2010, 2011, and 2016 respectively. He was a visiting scholar at UC Berkeley's Wireless Research Center from 2013 to 2014. He was a lecturer in the Electrical Engineering department for Caltech's popular machine learning project course in 2017. He is currently a postdoctoral scholar in the Electrical Engineering and Computational and Mathematical Sciences departments at Caltech. His research interests include RF and millimeter-wave integrated circuits and computational electromagnetics for biomedical applications, wireless communications, and silicon photonics. He was a recipient of an NSF graduate research fellowship in 2010, the Analog Devices Outstanding Student Designer Award in 2012, and the Caltech Leadership Award in 2017.
Host: Murali Annavaram, annarvarm@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
EE Seminar - Trustworthy Autonomy: Algorithms for Human-Robot Systems
Thu, Apr 19, 2018 @ 02:30 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Katherine Driggs-Campbell, Postdoctoral Research Scholar, Stanford Intelligent Systems Laboratory
Talk Title: Trustworthy Autonomy: Algorithms for Human-Robot Systems
Abstract: Autonomous systems, such as self-driving cars, are becoming tangible technologies that will soon impact the human experience. However, the desirable impacts of autonomy are only achievable if the underlying algorithms can handle the unique challenges humans present: People tend to defy expected behaviors and do not conform to many of the standard assumptions made in robotics. To design safe, trustworthy autonomy, we must transform how intelligent systems interact, influence, and predict human agents. In this work, we'll use tools from robotics, artificial intelligence, and control to explore and uncover structure in complex human-robot systems to create more intelligent, interactive autonomy.
In this talk, I'll present on robust prediction methods that allow us to predict driving behavior over long time horizons with very high accuracy. These methods have been applied to intervention schemes for semi-autonomous vehicles and to autonomous planning that considers nuanced interactions during cooperative maneuvers. I'll also present a new framework for multi-agent perception that uses people as sensors to improve mapping. By observing the actions of human agents, we demonstrate how we can make inferences about occluded regions and, in turn, improve control. Finally, I'll present on recent efforts on validating stochastic systems, merging deep learning and control, and implementing these algorithms on a fully equipped test vehicle that can operate safely on the road.
Biography: Katie is currently a Postdoctoral Research Scholar at the Stanford Intelligent Systems Laboratory in the Aeronautics and Astronautics Department. She received a B.S.E. with honors from Arizona State University in 2012 and an M.S. from UC Berkeley in 2015. In May of 2017, she earned her PhD in Electrical Engineering and Computer Sciences from the University of California, Berkeley, advised by Professor Ruzena Bajcsy. Her thesis was entitled "Tools for Trustworthy Autonomy: Robust Prediction, Intuitive Control, and Optimized Interaction," which contributed to the field of autonomy, by merging ideas robotics, transportation, and control to address problems associated with human-in-the-loop. Her work considers the integration of autonomy into human dominated fields, in terms of safe interaction, with a strong emphasis on novel modeling methods, experimental design, robust learning, and control frameworks. She received the Demetri Angelakos Memorial Achievement Award for her contributions to the community, has instigated many events and groups for women in STEM, including founding a group for Women in Intelligent Transportation Systems, and was selected for the Rising Stars in EECS program in 2017.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
Epstein Institute Seminar, ISE 651
Thu, Apr 19, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Rüdiger Schultz, Professor, University of Duisburg-Essen, Germany
Talk Title: Applied Optimization - Certainly Uncertain
Host: Prof. Suvrajeet Sen
More Information: April 19, 2018_Schultz.pdf
Location: GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
CAIS Seminar: Dr. Vipin Kumar (University of Minnesota) – Big Data in Climate and Earth Sciences: Challenges and Opportunities for Machine Learning
Thu, Apr 19, 2018 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Vipin Kumar, University of Minnesota
Talk Title: Big Data in Climate and Earth Sciences: Challenges and Opportunities for Machine Learning
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: A massive amount of data about Earth and its environment is continuously being generated by a large number of Earth observing satellites as well as physics-based earth system models running on large-scale computational platforms. These datasets offer huge potential for understanding how the Earth's climate and ecosystem have been changing and how they are being impacted by humans' actions. This talk will discuss various challenges involved in analyzing these massive datasets as well as opportunities they present for both advancing machine learning as well as the science of climate change in the context of monitoring the state of the tropical forests and surface water on a global scale.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Dr. Vipin Kumar is a Regents Professor and holds William Norris Chair in the department of Computer Science and Engineering at the University of Minnesota. His research interests include data mining, high-performance computing, and their applications in climate/ecosystems and health care. He is currently leading an NSF Expedition project on understanding climate change using data science approaches.
Host: Milind Tambe
Location: Mark Taper Hall Of Humanities (THH) - 301
Audiences: Everyone Is Invited
Contact: Computer Science Department
-
The Explosion in Neural Network Chips
Fri, Apr 20, 2018 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Trevor Mudge, University of Michigan, Ann Arbor
Talk Title: The Explosion in Neural Network Chips
Abstract: Until recently the conventional wisdom was that proposing a new chip startup in the US was a bad bet. Recently that perception has changed. There are dozens of startups that have found funding for new chip architectures that perform neural network computations much faster while consuming less power than general purpose CPUs. In fact, over 1.5 billion dollars in venture funding has already been dispersed for such startups. There are several factors behind this change of heart. First has been a slowing of Moore's Law that has made application specific computers more attractive. Second is the existence of application specific computers that could easily be repurposed, as exemplified by Digital Signal Processors and Graphics Processors. Finally, the presence of independent foundries such as the Taiwan Semiconductor Manufacturing Company and the United Microelectronics Corporation removed the need for every chip startup to build its own multi-billion dollar fabrication facility. In this talk I will discuss the reasons for this explosion starting with an overview of the problems these machines are targeting. I will then examine the aforementioned factors in more detail. Lastly, I will outline the co-design process that has led to many of the existing solutions. My concluding remarks will discuss the barriers to the success of these new architectures.
Biography: Trevor Mudge received the Ph.D. in Computer Science from the University of Illinois, Urbana. He is now the Bredt Family Professor of Computer Science and Engineering at the University of Michigan, Ann Arbor. He is author of numerous papers on computer architecture, programming languages, VLSI design, and computer vision. He has also chaired 54 theses in these areas. In 2014 he received the ACM/IEEE CS Eckert-Mauchly Award and the University of Illinois Distinguished Alumni Award. He is a Life Fellow of the IEEE, a Fellow of the ACM, and a member of the IET and the British Computer Society.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
-
W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM
Fri, Apr 20, 2018 @ 11:00 AM - 12:00 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Shaun Arora, Managing Director and Co-founder, Make in LA
Talk Title: Building a Lean Hardware Startup
Host: Dr. Prata & EHP
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Su Stevens
-
NL Seminar-Language as a Scaffold for Visual Recognition
Fri, Apr 20, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Mark Yatskar , AI2
Talk Title: Language as a Scaffold for Visual Recognition
Series: Natural Language Seminar
Abstract: In this talk we propose to use natural language as a guide for what people can perceive about the world from images and what ultimately machines should aim to see as well. We discuss two recent structured prediction efforts in this vein: scene graph parsing in Visual Genome, a framework derived from captions, and visual semantic role labeling in imSitu, a formalism built on FrameNet and WordNet. In scene graph parsing, we examine the problem of modeling higher order repeating structure motifs and present new state of the art baselines and methods. We then look at the problem semantic sparsity in visual semantic role labeling: infrequent combinations of output semantics are frequent. We present new compositional and data-augmentation methods for dealing with this challenge, significantly improving on prior work.
Biography: Mark Yatskar is a post-doc at the Allen Institute for Artificial Intelligence and recipient of their Young Investigator Award. His primary research is in the intersection of language and vision, natural language generation, and ethical computing. He received his Ph.D. from the University of Washington with Luke Zettlemoyer and Ali Farhadi and in 2016 received the EMNLP best paper award and his work has been featured in Wired and the New York Times.
Host: Nanyun Peng
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
-
SSE Systems Leadership Series
Mon, Apr 23, 2018 @ 10:00 AM - 12:00 PM
Systems Architecting and Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Shane Henderson, Professor and Director - School of Operations Research and Information Engineering, Cornell University
Talk Title: Citi Bike - Planning through a Combination of Continuous, Discrete, and Simulation Optimization
Abstract: The Cornell School of Operations Research and Information Engineering has been working with the bike-sharing company Citi Bike since Citi Bike began operations in New York City in 2013. We provide data analysis and advice about strategy and operations, not just to Citi Bike, but also to its parent company Motivate that operates several bike-sharing programs around the USA. I will describe some of our modeling work with Citi Bike, focusing on a suite of models (not just simulation models) that informs the decision about where to position both racks and bikes around the approximately 600 stations in NYC. Joint work with Daniel Freund, Nanjing Jian, Eoin OMahony and David Shmoys.
The Systems Leadership Series is a series of interactive conversations with leading systems thinkers who explore and examine the nature and complexity of systems that modern society depends upon. The series is an unparalleled learning opportunity as prominent speakers come to share cutting edge ideas, leadership styles and personal philosophies with students and faculty members.
Biography: Shane G. Henderson is professor and director of the School of Operations Research and Information Engineering at Cornell University. He has previously held positions in the Department of Industrial and Operations Engineering at the University of Michigan and the Department of Engineering Science at the University of Auckland. He is the editor in chief of Stochastic Systems. He has served as chair of the INFORMS Applied Probability Society, and as simulation area editor for Operations Research. He is an INFORMS Fellow. His research interests include discrete-event simulation, simulation optimization, and emergency services planning.
Host: Stevens Institute of Technology School of Systems and Enterprises
More Info: https://www.stevens.edu/events/systems-leadership-series-shane-henderson-cornell-university
Webcast: Register at the event link.Location: Online via WebEX
WebCast Link: Register at the event link.
Audiences: Everyone Is Invited
Contact: James Moore II
Event Link: https://www.stevens.edu/events/systems-leadership-series-shane-henderson-cornell-university
-
PhD Academic Career Mentoring Panel Series
Mon, Apr 23, 2018 @ 12:00 PM - 01:30 PM
Viterbi School of Engineering Doctoral Programs
Conferences, Lectures, & Seminars
Speaker: Panel moderated by Timothy Pinkston, Vice Dean of Academic Affairs,
Talk Title: Preparing for and Landing a Faculty Position
Abstract: A panel of graduating Ph.D. students and a postdoc, will discuss "Preparing For, and Landing a Faculty Position." Moderated by Vice Dean Timothy Pinkston, the panelists will discuss key strategies for the early, middle, and latter stages of your PhD and postdoc that will help you prepare for landing a faculty position. A Q&A will be included in the panel discussion. A boxed lunch will be provided to all registered participants
More Info: https://viterbigrad.usc.edu/instructional-support/events-workshops/phd-academic-career-mentoring-panel-series/
More Information: USC Panel Flyer.pdf
Location: 102
Audiences: Ph.D. and Postdoctoral
Contact: Tracy Charles
-
Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Apr 23, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Steven Brunton, University of Washington
Talk Title: Data-Driven Discovery and Control of Nonlinear Systems
Series: Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: The ability to discover physical laws and governing equations from data is one of humankind's greatest intellectual achievements. A quantitative understanding of dynamic constraints and balances in nature has facilitated rapid development of knowledge and enabled advanced technology, including aircraft, combustion engines, satellites, and electrical power. There are many more critical data-driven problems, such as understanding cognition from neural recordings, inferring patterns in climate, determining stability of financial markets, predicting and suppressing the spread of disease, and controlling turbulence for greener transportation and energy. With abundant data and elusive laws, data-driven discovery of dynamics will continue to play an increasingly important role in these efforts.
This work develops a general framework to discover the governing equations underlying a dynamical system simply from data measurements, leveraging advances in sparsity-promoting techniques and machine learning. The resulting models are parsimonious, balancing model complexity with descriptive ability while avoiding overfitting. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions. This perspective, combining dynamical systems with machine learning and sparse sensing, is explored with the overarching goal of real-time closed-loop feedback control of complex systems. Connections to modern Koopman operator theory are also discussed.
Biography: Steven L. Brunton is an Assistant Professor of Mechanical Engineering and a Data Science Fellow at the eScience Institute at the University of Washington in Seattle. He received a B.S. in Mathematics with a minor in Control and Dynamical Systems from Caltech in 2006, and received a Ph.D. in Mechanical and Aerospace Engineering from Princeton in 2012. His research interests include data-driven modeling and control, dynamical systems, sparse sensing and machine learning applied to complex systems in fluid dynamics, optics, neuroscience, bio-locomotion, and renewable energy.
Host: Eva Kanso, kanso@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
-
Astani Civil and Environmental Engineering Seminar
Tue, Apr 24, 2018 @ 11:00 AM - 12:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Clemens Heitzinger, Technical University of Vienna
Talk Title: Bayesian Inversion for Sensing in Bio and Nanotechnology
Host: Dr. Roger Ghanem
More Information: CEE Seminar _Dr. Clemens Heitzinger.pdf
Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
-
Deterministic Random Matrices
Wed, Apr 25, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ilya Soloveychik, School of Engineering and Applied Sciences, Harvard University
Talk Title: Deterministic Random Matrices
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Random matrices have become a very active area of research in the recent years and have found enormous applications in modern mathematics, physics, engineering, biological modeling, and other fields. In this work, we focus on symmetric sign (+/-1) matrices (SSMs) that were originally utilized by Wigner to model the nuclei of heavy atoms in mid-50s. Assuming the entries of the upper triangular part to be independent +/-1 with equal probabilities, Wigner showed in his pioneering works that when the sizes of matrices grow, their empirical spectra converge to a non-random measure having a semicircular shape. Later, this fundamental result was improved and substantially extended to more general families of matrices and finer spectral properties. In many physical phenomena, however, the entries of matrices exhibit significant correlations. At the same time, almost all available analytical tools heavily rely on the independence condition making the study of matrices with structure (dependencies) very challenging. The few existing works in this direction consider very specific setups and are limited by particular techniques, lacking a unified framework and tight information-theoretic bounds that would quantify the exact amount of structure that matrices may possess without affecting the limiting semicircular form of their spectra.
From a different perspective, in many applications one needs to simulate random objects. Generation of large random matrices requires very powerful sources of randomness due to the independence condition, the experiments are impossible to reproduce, and atypical or non-random looking outcomes may appear with positive probability. Reliable deterministic construction of SSMs with random-looking spectra and low algorithmic and computational complexity is of particular interest due to the natural correspondence of SSMs and undirected graphs, since the latter are extensively used in combinatorial and CS applications e.g. for the purposes of derandomization. Unfortunately, most of the existing constructions of pseudo-random graphs focus on the extreme eigenvalues and do not provide guaranties on the whole spectrum. In this work, using binary Golomb sequences, we propose a simple completely deterministic construction of circulant SSMs with spectra converging to the semicircular law with the same rate as in the original Wigner ensemble. We show that this construction has close to lowest possible algorithmic complexity and is very explicit. Essentially, the algorithm requires at most 2log(n) bits implying that the real amount of randomness conveyed by the semicircular property is quite small.
Biography: Ilya Soloveychik received his BSc degree in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology, Moscow, Russia in 2007, the MSc degree in Mathematics and the PhD degree in Electrical Engineering from the Hebrew University of Jerusalem, Israel in 2013 and 2016, respectively. He is currently a Fulbright postdoctoral fellow with the Harvard School of Engineering and Applied Sciences. His research interests include random matrix theory, high-dimensional statistics and signal processing, and graphical models. He received the Potanin Scholarship for excellence in studies in 2005, the Klein Prize and the Kaete Klausner Scholarship in 2011. In 2015 he was awarded the Feder Family Prize for outstanding research in the field of Communications Technology and in 2016 - the Wolf Foundation Prize for excellence in studies.
Host: Professor Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
-
EE Seminar: Cryptographic Primitives for Hardware Security
Thu, Apr 26, 2018 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ling Ren, MIT CSAIL
Talk Title: Cryptographic Primitives for Hardware Security
Abstract: Hardware plays a critical role in today's security landscape. Every protocol with security or privacy guarantees inevitably includes some hardware in its trusted computing base. The increasing number of vulnerability disclosures calls for a more rigorous approach to secure hardware designs. In this talk, I will present several cryptographic primitives to enhance the security of hardware.
I will first discuss the use of Physically Obfuscated Keys (POK) to strengthen the security of private keys. In particular, I will present a computational fuzzy extractor based on the Learning Parity with Noise (LPN) problem. Our construction uses stability information as a trapdoor to correct a constant fraction of POK errors efficiently. Next, I will describe our work on Oblivious RAM (ORAM), a cryptographic primitive to prevent access pattern leakage. I will present both architectural and algorithmic improvements to ORAM.
While hardware is often trusted as a line of defense, it can also be utilized by attackers. The advent of ASIC hash units calls into question the security of hash functions and proof-of-work protocols. I will describe bandwidth-hard functions to achieve ASIC resistance and briefly touch on my other projects in blockchains and consensus.
Biography: Ling Ren is a final year graduate student at Massachusetts Institute of Technology. He received his Master's degree from Massachusetts Institute of Technology and Bachelor's degree from Tsinghua University. His research interests span computer security, cryptography, computer architecture and distributed computing. He received the best student paper award at CCS 2013.
Host: Bhaskar Krishnamachari, bkrishna@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
-
CCI Seminar: Karan Motwani (Starbucks Coffee Company) – Developing Blockchain Solutions Beyond Cryptocurrency
Thu, Apr 26, 2018 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Karan Motwani, Starbucks Coffee Company
Talk Title: Developing Blockchain Solutions Beyond Cryptocurrency
Series: USC Center for Cyber-Physical Systems and the Internet of Things Seminar Series
Abstract: Talk will cover:
- Fundamentals of Blockchain -“ highlights key differences between few Blockchain platforms.
- Considerations when developing Blockchain solutions with emphasis on Ethereum
- Components required to deploy a fully functioning Blockchain solution
- Evaluating use cases which can benefit from Blockchain implementation
- Challenges around Blockchain technology and its future ahead.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Karan Motwani is an IT Leader with 17+ years of experience in consulting, architecture, engineering, and strategic leadership roles. He has worked with companies from Europe, Latin America, Asia, Middle East and the United States on supply chain and finance solutions. From this experience, he brings an entrepreneurial perspective, and an ability to work across business and engineering on Blockchain application to Supply chain and Finance scenarios.
Host: Bhaskar Krishnamachari
Location: Michelson Center for Convergent Bioscience (MCB) - Michelson Building (MCB) 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
-
Epstein Institute Seminar, ISE 651
Thu, Apr 26, 2018 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Osman Ozaltin, Assistant Professor, North Carolina State University
Talk Title: Improving Patient Safety in the External Beam Radiation Therapy Process
Host: Dr. Julie Higle
More Information: April 26, 2018_Ozaltin.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
-
EE-EP Seminar - Maysam Ghovanloo, Friday, April 27th at 2pm in EEB 132
Fri, Apr 27, 2018 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Maysam Ghovanloo, Georgia Institute of Technology
Talk Title: Cutting Edge Examples of Medical Device-on-a-Chip
Abstract: For medical devices that need to be implanted or positioned inside the human body to deliver a therapy, size and functionality are among the most important parameters, affecting key aspects of the device, such as feasibility, level of invasiveness, side effects, and safety, ability to reach the desired anatomical target, and efficacy in carrying out intended functions, such as imaging, recording biological parameters, delivering drugs, or applying stimuli, or a combination of these as part of a medical intervention. on the On the other hand, microelectronic devices, integrated circuit design, and system-level architectures have advanced to the point that combining multiple functions in a variety of domains from low noise analog readout, to on-chip digital processing, RF connectivity, power management, and precise control of physical outputs on a monolithic piece of silicon has become quite routine, in an approach referred to as the system-on-a-chip (SoC). In this talk, I will present a few examples of applying the well-established SoC technology towards design and development of cutting edge medical devices that are fit to be implanted or delivered inside the body, while being supported by system blocks outside of the body, to either create de novo medical interventions or significantly improve the existing therapies. I refer to these as the medical device-on-a-chip (MDoC) approach, and also propose the pathway towards design concept, preliminary steps, and evaluation plans for new MDoC technologies that would enable new therapies and interventions that are not feasible today.
Biography: Maysam Ghovanloo received the B.S. degree in electrical engineering from the University of Tehran in 1994, and the M.S. degree in biomedical engineering from the Amirkabir University of Technology, Tehran, Iran in 1997. He also received the M.S. and Ph.D. degrees in electrical engineering from the University of Michigan, Ann Arbor, in 2003 and 2004, respectively.
Dr. Ghovanloo developed the first modular Patient Care Monitoring System in Iran and started a company to manufacture research instruments for electrophysiology and pharmacology labs. From 2004 to 2007 he was an assistant professor in the Department of ECE at the North Carolina State University, Raleigh, NC. Since 2007 he has been with the Georgia Tech's School of Electrical and Computer Engineering, where he is a professor and the founding director of the GT-Bionics Lab. In 2012 he started Bionic Sciences Inc., a technology transfer company, where he serves as the CTO. He has authored or coauthored more than 200 peer-reviewed conference and journal publications on implantable microelectronic devices, integrated circuits and microsystems for medical applications, and modern assistive/rehabilitation technologies. He also holds 8 issued patents.
Prof. Ghovanloo was a recipient of the National Science Foundation CAREER Award, the Tommy Nobis Barrier Breaker Award for Innovation, and Distinguished Young Scholar Award from the Association of Professors and Scholars of Iranian Heritage. He is an Associate Editor of the IEEE Transactions on Biomedical Engineering and IEEE Transactions on Biomedical Circuits and Systems. He serves on the Senior Editorial Board of the IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS). He served as an Associate Editor of IEEE Transactions on Circuits and Systems, Part II, as well as a Guest Editor for the IEEE Journal of Solid-State Circuits and IEEE Transactions on Neural Systems and Rehabilitation Engineering. He chaired the IEEE Biomedical Circuits and Systems (BioCAS 2015) in Atlanta, GA, and currently co-chairs the technical program committee for BioCAS 2018 in Cleveland, OH. He is also serving on the Analog subcommittee of the Custom Integrated Circuits Conf. (CICC).
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
-
Astani Civil and Environmental Engineering Seminar
Fri, Apr 27, 2018 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Amir Eftekharian , Astani CEE Ph.D. Student
Talk Title: Wave Structure Interaction: Kinematics Properties of Wave Overtopping Breakwaters and its Impacts in Harbor Regions
Abstract: See Attachment
More Information: Amirhossein Eftekharian 4.27 seminar announcement.pdf
Location: Ray R. Irani Hall (RRI) - 101
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
-
NL-Seminar Extracting and Aligning Quantitative Data with Tex
Fri, Apr 27, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jay Pujara, USC/ISI
Talk Title: Extracting and Aligning Quantitative Data with Tex
Series: Natural Language Seminar
Abstract: Quantitative data, such as time series and numerical attribute data, often play a crucial role in understanding the world and validating factual statements. Unfortunately, quantitative datasets are often expressed in diverse formats that exhibit significant variation, posing difficulties to machine reading approaches. Furthermore, the scant context that accompanies these data often makes it difficult to relate the quantitative data with broader ideas. Finally, the vast amount of quantitative data make it difficult for humans to find, understand, or access. In this talk, I highlight my recent work, which focuses on developing general approaches to extracting quantitative data from structured sources, creating high level descriptions of these sources, and aligning quantitative data with textual and ontological labels.
Biography: Jay Pujara is a research scientist at the University of Southern California's Information Sciences Institute whose principal areas of research are machine learning, artificial intelligence, and data science. He completed a postdoc at UC Santa Cruz, earned his PhD at the University of Maryland, College Park and received his MS and BS at Carnegie Mellon University. Prior to his PhD, Jay spent six years at Yahoo! working on mail spam detection, and he has also worked at Google, LinkedIn and Oracle. Jay is the author of over thirty peer-reviewed publications and has received three best paper awards for his work. He is a recognized authority on knowledge graphs, and has organized the Automatic Knowledge Base Construction AKBC and Statistical Relational AI StaRAI workshops, presented tutorials on knowledge graph construction at AAAI and WSDM, and had his work featured in AI Magazine.
Host: Nanyun Peng
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
-
Rapid, Efficient, and Robust Neuroimage Analysis with Deep Neural Networks
Mon, Apr 30, 2018 @ 11:30 AM - 12:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mert R. Sabuncu, Electrical and Computer Engineering, Cornell University
Talk Title: Rapid, Efficient, and Robust Neuroimage Analysis with Deep Neural Networks
Series: Medical Imaging Seminar Series
Abstract: Abstract: Neuroimaging is entering a new era of unprecedented scale and complexity. Soon, we will have datasets including brain images from more than 100,000 individuals. The fundamental challenges in analyzing and exploiting these data are going to be computational. Today, widely-used traditional neuroimage analysis tools, such as FreeSurfer or FSL, are computationally demanding and offer limited flexibility, while cutting-edge tools based on modern machine learning techniques require large amounts of annotated training data, and/or are untested at scale. In this talk, I will present our recent work on two fundamental image analysis problems: registration and segmentation. In image registration, I will introduce a novel framework that allows us to train a neural network that rapidly computes a smooth and invertible nonlinear (diffeomorphic) deformation that aligns two input images, in an unsupervised fashion (i.e. without using ground-truth registrations). I will show experiments on 7000+ brain MRI scans with state-of-the-art results. In the second part, I will present a new segmentation framework that flexibly handles multiple labeling protocols, and generalizes well to new datasets and new segmentation labels, with little additional training.
Biography: Mert R. Sabuncu is a faculty member of Cornel's School of Electrical Engineering and Computer Engineering.At Cornell, Mert directs a lab that focuses on biomedical image analysis for scientific (e.g. brain mapping) and clinical (e.g., computer-aided diagnosis) applications.Mert's research employs and contributes to the toolkits of machine learning, image processing, computer vision, and other modern computational methods.Mert has a Ph.D. from Princeton Electrical Engineering and was post-doc at MIT, where he worked with Polina Golland. Before joining Cornell, he was a faculty member at the A.A. Martinos Center for Biomedical Imaging (Harvard Medical School and Massachusetts General Hospital).
Host: Professor Richard Leahy
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
