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Conferences, Lectures, & Seminars
Events for April
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CS Colloquium: Austin Benson (Stanford) -Tools for higher-order network analysis
Mon, Apr 03, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Austin Benson , Stanford University
Talk Title: Tools for higher-order network analysis
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Networks are a fundamental model of complex systems in biology, neuroscience, engineering, and social science. Networks are typically described by lower-order connectivity patterns that are captured at the level of individual nodes and edges. However, higher-order connectivity patterns captured by small subgraphs, or network motifs, describe the fundamental structures that control and mediate the behavior of many complex systems. In this talk, I will discuss several higher-order analyses based on higher-order connectivity patterns that I have developed to gain new insights into network data. Specifically, I will introduce a motif-based clustering methodology, a generalization of the classical network clustering coefficient, and a formalism for temporal motifs to study temporal networks. I will also show applications of higher-order analysis in several domains including ecology, biology, transportation, neuroscience, social networks, and human communication.
Biography: Austin Benson is a PhD candidate at Stanford University in the Institute for Computational and Mathematical Engineering where he is advised by Professor Jure Leskovec of the Computer Science Department. His research focuses on developing data-driven methods for understanding complex systems and behavior. Broadly, his research spans the areas of network science, applied machine learning, tensor and matrix computations, and computational social science. Before Stanford, he completed undergraduate degrees in Computer Science and Applied Mathematics at the University of California, Berkeley. Outside of the university, he has spent summers interning at Google (four times), Sandia National Laboratories, and HP Labs.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Seminars in Biomedical Engineering
Mon, Apr 03, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Song Li, PhD, Chancellor Professor & Dept. Chair, UCLA, Dept. of Bioengineering & Medicine
Talk Title: Microbiology Application
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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CS Colloquium: Stephan Mandt (Disney Research) - Next generation variational inference: algorithms, models, and applications
Mon, Apr 03, 2017 @ 01:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Stephan Mandt, Disney Research
Talk Title: Next generation variational inference: algorithms, models, and applications
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Probabilistic modeling is a powerful paradigm in machine learning. In this field, we assume a generative process in order to explain our observations, and then use a Bayesian inference algorithm to reason about its parameters. Probabilistic modeling has become scalable due to stochastic variational inference which reduces Bayesian inference to non-convex stochastic optimization. This talk focuses on two new inference algorithms: variational tempering-an algorithm that operates on several artificial temperatures simultaneously to find better local optima, and constant SGD-a scalable inference algorithm with applications to hyperparameter optimization. I will then present several new models that have become tractable due to modern variational inference with applications in text modeling, recommendations, and computer vision. I will show how a probabilistic view on Google's word2vec algorithm allows for extensions to other types of high dimensional data and show new applications: analyzing supermarket shopping data, movie ratings, and tracking semantic changes of individual words over centuries of digitized books. Finally, I will show how factorized variational autoencoders allow us to analyze audience reactions to movies.
Biography: Stephan Mandt is a research scientist at Disney Research Pittsburgh, where he leads the statistical machine learning group. From 2014 to 2016 he was a postdoctoral researcher with David Blei at Columbia University, and from 2012 to 2014 a PCCM postdoctoral fellow at Princeton University. Stephan did his Ph.D. with Achim Rosch at the Institute for Theoretical Physics at the University of Cologne, supported by a fellowship of the German National Merit Foundation. His research interests include scalable approximate Bayesian inference and machine learning for media analytics.
Host: Fei Sha
Location: Kaprielian Hall (KAP) - 140
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Apr 03, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Oleg Sokolsky, Research Professor, University of Pennsylvania
Talk Title: Behavior Modeling in Patient-in-the-Loop Medical CPS
Abstract: Human-in-the-loop cyber-physical systems (CPS) is an active area of research. As the level of autonomy in systems we use every day is rapidly increasing, the problems of human-automation interaction and of trust in technology are becoming more important. In medical CPS, interactions between the human and technology happen both through behavior as well as through patient physiology. This talk motivates the need for modeling and analysis techniques that take both behavioral and physiological interactions into consideration. We present a case study of diabetic patients interacting with smart insulin pumps and consider how behavioral modeling and analysis can impact treatment outcomes.
Biography: Oleg Sokolsky is a Research Professor of Computer and Information Science at PRECISE Center, University of Pennsylvania. His research interests include applications of formal methods and runtime verification to the design and analysis. He received a Ph.D. in Computer Science from State University of New York at Stony Brook.
Host: Paul Bogdan and Chao Wang
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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Improving Sensitivity and Spatial Coverage of Myocardial Arterial Spin Labeling
Tue, Apr 04, 2017 @ 03:00 AM - 04:00 PM
Conferences, Lectures, & Seminars
Speaker: Terrence Jao, University of Southern California
Talk Title: Improving Sensitivity and Spatial Coverage of Myocardial Arterial Spin Labeling
Series: Medical Imaging Seminar Series
Biography: Terrence Jao is a MD/PhD student in the department of biomedical engineering working under Prof. Krishna Nayak at the Magnetic Resonance Engineering Laboratory. His research interests are in pulse sequence development, image reconstruction, and cardiac imaging. He received a B.S. from Johns Hopkins University in 2008.
Host: Professor Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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USC Stem Cell Seminar: Rafi Kopan, Cincinnati Children's Hospital
Tue, Apr 04, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Rafi Kopan, Cincinnati Children's Hospital
Talk Title: TBD
Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series
Host: USC Stem Cell
More Info: http://stemcell.usc.edu/events
Webcast: http://keckmedia.usc.edu/stem-cell-seminarWebCast Link: http://keckmedia.usc.edu/stem-cell-seminar
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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CS Colloquium: Jelena (Marasevic) Diakonikolas (Boston University ) -From Networked Systems to Theory and Back: Full-Duplex Wireless and Beyond
Tue, Apr 04, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jelena (Marasevic) Diakonikolas, Boston University
Talk Title: From Networked Systems to Theory and Back: Full-Duplex Wireless and Beyond
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
As our ambitions to build larger and more complex networked systems are ever increasing, the following three general trends can be observed: (i) wireless data traffic is growing, (ii) the number of devices connecting to the networked systems is surging, and (iii) networks are increasingly used not only for communication, but also for computation. I will present results that are motivated by these trends and that span different aspects of networked systems: from modeling of the system components, over rigorous algorithm design and analysis, to testbed development and performance evaluation.
The unprecedented growth of the wireless traffic over scarce spectrum resources prompts the development of more spectrum-efficient techniques. On the roadmap to 5G wireless standards, full-duplex has been recognized as one of the key technologies for improving the spectrum efficiency. I will present the results on principled design of full-duplex systems that were obtained as part of a cross-disciplinary project "Full-duplex wireless: From integrated circuits to networks" (FlexICoN), which I co-initiated at Columbia. In particular, I will describe a mathematical model of an integrated full-duplex receiver developed within FlexICoN and present resource allocation algorithms tailored to the realistic receiver models. Then, I will highlight the experimental results obtained in a custom-designed full-duplex wireless testbed, developed for the evaluation of our full-duplex hardware and resource allocation and scheduling algorithms.
Further, I will highlight how the growing scale of networked systems raises the need for fast fair resource allocation algorithms and describe our novel algorithmic results for addressing these issues. Finally, I will describe some of the challenges in networks involving communication and computation, my ongoing work in this area, and future directions.
Biography: Jelena (Marasevic) Diakonikolas is a Postdoctoral Associate at Boston University and a Visiting Scholar at Massachusetts Institute of Technology. Her research focuses on principled design of networked systems. Her research on full-duplex wireless systems was awarded a Qualcomm 2015 Innovation Fellowship, was featured in IEEE Spectrum, and resulted in several invited papers. She was selected as an MIT EECS Rising Star in 2015, and named one of the "10 Women in Networking/Communications That You Should Watch" in 2016. She designed the first cellular networking hands-on lab, winning GENI GREE 2013 Best Educational Paper Award. Jelena completed her Ph.D. and M.S. degrees at Columbia University, with an M.S. Award of Excellence and a Jacob Millman Prize for Excellence in Teaching Assistance. She obtained her Bachelor's degree from University of Belgrade, where she held the two most prestigious government-awarded fellowships.
Host: CS Department
More Information: headshot.jpg
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Matthew Gilbert, Nano Science & Technology Seminar Series, Tuesday, April 4 at 2:00pm in EEB 248
Tue, Apr 04, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Matthew J. Gilbert, University of Illinois Urbana-Champaign
Talk Title: Topological Energy Transduction
Abstract: Within the CMOS architecture, the interconnected devices may either be categorized as an "active" device, which produces energy in the form of a current or a voltage, or a "passive" device, which stores or maintains energy in the form of a current or voltage. The societal demand for smaller sized electronic devices, such as computers and cellular phones, with improved functionality has forced not only the sizes of the constituent components of CMOS information processing technology to rapidly shrink, but for the operational frequencies to increase. While it has been possible to reduce the size of active CMOS devices, passive devices have not seen the same reduction in size. Of the passive devices (e.g. resistors, capacitors and inductors) used in CMOS technologies, the circuit element that consumes the most area on a circuit board while simultaneously finding the least success in miniaturization is the inductor. In this talk, we will present a novel method for energy transduction that utilizes the interplay between magnetism and topology on the surface of a newly discovered materials, referred to as time-reversal invariant topological insulators, to create a paradigmatically different inductor. Using a novel self-consistent simulation that couples AC non-equilibrium Green functions to fully electrodynamic solutions of Maxwell's equations, we demonstrate excellent inductance densities up to terahertz frequencies thereby providing a potential solution to an eminent grand challenge.
Biography: Matthew J. Gilbert is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He is affiliated with the Micro and Nanotechnology Laboratory, the Department of Physics and the Institute for Condensed Matter Theory at UIUC. His research broadly focuses on theoretically elucidating new phenomena in emergent nanoscale systems with the goal of developing new types of nanoelectronic and nanophotonic devices and functionality for next-generation information processing systems. The majority of his current work revolves around understanding the properties of topological materials, including insulators, semimetals and superconductors, with the goal of understanding their potential role in the post-CMOS device landscape. This research also includes examinations into the appearance and stability of unconventional superconductivity and non-Abelian anyons, such as Majorana and parafermions, in topological systems for the purposes of topological quantum computation. His emerging research interests include: the role of interactions in the classification and properties of topological systems, dissipation and relaxation in non-equilibrium materials and systems, transport properties and phenomena in 2D materials particularly those under strain, energy harvesting using topological materials, and designer layered quantum materials. He has authored more than 70-refereed publications, and has given presentations at over 50 international conferences.
Host: Wang, Zhou, Cronin, Wu - MHI
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Seminar, ISE 651
Tue, Apr 04, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Elizabeth Tseng, Senior Staff Scientist, Pacific Biosciences
Talk Title: Applying Long Read DNA Sequencing for Genome Assembly and Transcriptome Analysis: Existing Solutions and Open Problems
Host: Prof. Meisam Razaviyayn
More Information: April 4, 2017_Tseng.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Astani Civil and Environmental Engineering Seminar
Wed, Apr 05, 2017 @ 11:00 AM - 12:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Monica Kohler, Research Assistant Professor, Department of Mechanical and Civil Engineering, Caltech
Talk Title: Damage Detection in Buildings Using
More Information: Kohler Seminar Announcement April 5.pdf
Location: Kaprielian Hall (KAP) - 140
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Matthew Gilbert - Nano Science & Technology Seminar Series, Wednesday, April 5th at 2:00pm in KAP 209
Wed, Apr 05, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Matthew J. Gilbert, University of Illinois Urbana-Champaign
Talk Title: Unconventional Superconductivity in Topological Heterostructures
Abstract: The search for materials and systems that exhibit unconventional superconductivity, or superconductivity beyond the canonical s-wave pairing as predicted in BCS theory, is one of the most active areas within condensed matter physics. This effort has been reinvigorated by the interesting properties inherent to a new class of materials that possess topological phases. A topological phase is unique in that it does not break any of the underlying symmetries of the system and cannot be described by a local order parameter. In other words, the inherent properties of the system cannot be changed by adiabatic shifts in materials parameters unless the system passes a quantum critical point associated with a phase transition. More recently, this search has taken on additional significance due to the fact that systems that possess unconventional superconductivity may enable a new type of fault tolerant quantum information processing that may significantly increase computing power when compared to traditional information processing. In this talk, I will discuss the appearance and signatures of unconventional superconductivity and review some of the most prominent systems that have been predicted to exhibit unconventional superconductivity. In particular, I will focus on heterostructures containing s-wave superconductors and proximity-coupled 3D time-reversal invariant topological insulators. I will explain some of the experimentally relevant conditions that must be satisfied in order to observe the features of unconventional superconductivity and conclude by examining the potential for finding unconventional superconductivity in emergent topological materials such as semimetals and crystalline insulators.
Biography: Matthew J. Gilbert is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He is affiliated with the Micro and Nanotechnology Laboratory, the Department of Physics and the Institute for Condensed Matter Theory at UIUC. His research broadly focuses on theoretically elucidating new phenomena in emergent nanoscale systems with the goal of developing new types of nanoelectronic and nanophotonic devices and functionality for next-generation information processing systems. The majority of his current work revolves around understanding the properties of topological materials, including insulators, semimetals and superconductors, with the goal of understanding their potential role in the post-CMOS device landscape. This research also includes examinations into the appearance and stability of unconventional superconductivity and non-Abelian anyons, such as Majorana and parafermions, in topological systems for the purposes of topological quantum computation. His emerging research interests include: the role of interactions in the classification and properties of topological systems, dissipation and relaxation in non-equilibrium materials and systems, transport properties and phenomena in 2D materials particularly those under strain, energy harvesting using topological materials, and designer layered quantum materials. He has authored more than 70-refereed publications, and has given presentations at over 50 international conferences.
Host: Wang, Zhou, Cronin, Wu - MHI
Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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MHI CommNetS seminar
Wed, Apr 05, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hamidreza Tavafoghi, University of Michigan
Talk Title: Dynamic Market Mechanisms for Wind Energy
Series: CommNetS
Abstract: We investigate the problem of market mechanism design for wind energy integration into the power grid. We show that the current static two-settlement market structure is not efficient for the integration of wind energy, and does not provide appropriate information for scheduling of flexible loads/reserves. We consider a dynamic two-step model with strategic seller(s) with wind generation and one buyer, who trade energy through a mechanism determined by a designer (ISO). The seller has private information about his technology and wind condition, which he learns dynamically over time. We consider the existing (static) forward and real-time mechanisms that take place at times T = 1 and T = 2, respectively. We propose a dynamic mechanism that provides a coupling between the outcomes of the forward and real-time markets, and show that the dynamic mechanism outperforms the forward and real-time mechanisms for a general objective of the designer. We demonstrate that the advantages of our proposed dynamic mechanism come from the designer's ability to price discriminate and the seller's exposure to penalty risk. Moreover, our proposed mechanism reveals (probabilistic) information about wind generation in advance so as to schedule flexible loads/reserves efficiently. We further analyze variants of the dynamic mechanism that guarantee no penalty risk for sellers, and/or monitor the wind condition.
Biography: Hamidreza Tavafoghi is a Ph.D. candidate in the Electrical Engineering and Computer Science department at the University of Michigan working with Prof. Demosthenis Teneketzis, where he also pursues a M.A. in Economics. His research interests lie in stochastic control, game theory, mechanism design, and strategic learning. Currently, he is working on the design and analysis of informational and monetary incentive mechanisms for cyber-physical systems with applications to power systems, transportation networks, and security. Hamidreza received his B.Sc. in Electrical Engineering from Sharif University of Technology, Tehran, Iran, 2011, and his M.Sc. in Electrical Engineering: Systems from the University of Michigan, 2013. He was awarded the Dow Sustainability Fellowship in 2015. He is a Silver medalist of 37th International Physics Olympiad, Singapore, 2006, and a Gold medalist of 18th National Physics Olympiad, Iran, 2005.
Host: Prof. Ashutosh Nayyar
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Aerospace & Mechanical Engineering Seminar
Wed, Apr 05, 2017 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Michael W. Plesniak, Professor, Department of Mechanical & Aerospace Engineering, The George Washington University
Talk Title: Fluid Dynamics of Phonation
Abstract: Speech production involves unsteady pulsatile flow and turbulent structures that affect the aeroacoustics and fluid-tissue interaction. The goal of our human phonation research program is to investigate the dynamics of flow past the vocal folds (VF) and the aerodynamic interaction with the VF. Over the course of the program we have studied static, driven and self-oscillating models of the VF system. Silicone-based, self-oscillating synthetic vocal fold (VF) models are fabricated with material properties representative of the different layers of human VFs and then evaluated experimentally in a life-size vocal tract simulator to replicate physiological conditions. Our experimental investigations utilize high-speed imaging, particle image velocimetry (PIV), pressure transducers and microphones, and the clinical Rothenberg mask. Studies are performed under both normal and pathological conditions of speech. In particular, recent attention has been focused on understanding the role of polyps (growths on the VF) in altering voice quality. This has led to very fundamental studies of 3D flow separation in pulsatile flows. We have also collaborated with colleagues in the Department of Speech and Hearing Sciences to better understand the effects of ageing on voice. Our overarching motivation for studying flow associated with phonation is to facilitate evaluation and design of treatment interventions and for surgical planning, i.e. to enable physicians to assess the outcomes of surgical procedures by using faithful computer simulations. Such simulations are on the horizon with the advent of increasingly more powerful high performance computing and cyberinfrastructure, but they still lack many of the necessary physical models. We also seek to inform non-surgical clinical treatment strategies of voice disorders.
Biography: Michael W. Plesniak is Professor and Chair of the Department of Mechanical & Aerospace Engineering at The George Washington University, with a secondary appointment in the Department of Biomedical Engineering. He was formerly Professor of Mechanical Engineering at Purdue University and Eugene Kleiner Professor for Innovation in Mechanical Engineering at Polytechnic University in Brooklyn, NY. He served as the Director of the Fluid Dynamics & Hydraulics program at the National Science Foundation from 2002-2006. Prof. Plesniak earned his Ph.D. degree from Stanford University, and his M.S. and B.S degrees from the Illinois Institute of Technology; all in Mechanical Engineering. Dr. Plesniak is a Fellow of AIAA, ASME, the American Physical Society (APS), the American Institute for Medical and Biological Engineering (AIMBE) and the Association for the Advancement of Science (AAAS). He has authored over two hundred fifty refereed archival publications, conference papers and presentations. He has presented numerous invited seminars and keynote addresses. His research group is currently studying the physics of phonation and cardiovascular flows. Dr. Plesniak is the Director of GW's Center for Biomimetics and Bioinspired Engineering. Prof. Plesniak was a recipient of the 2017 ASME Fluids Engineering Award, the 2011 NASA DC Space Grant Consortium's Outstanding STEM Faculty Award, awarded to faculty that make an outstanding contribution to STEM that goes above and beyond the classroom. Dr. Plesniak was also named the American Institute for Aeronautics and Astronautics, National Capital Section Engineer of the Year 2010-2011.
Host: Department of Aerospace and Mechanical Engineering
More Info: https://ame.usc.edu/about/seminars/
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
Event Link: https://ame.usc.edu/about/seminars/
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Lyman Handy Colloquia
Thu, Apr 06, 2017 @ 12:45 PM - 01:45 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Professor Tobias A. Schaedler, Senior Research Scientist, HRL Laboratories, LLC, Malibu, CA
Talk Title: Additive Manufacturing of Polymer-Derived Ceramics
Host: Dr. Andrea Hodge
Location: James H. Zumberge Hall Of Science (ZHS) - 159
Audiences: Everyone Is Invited
Contact: Aleessa Atienza
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AI Seminar
Fri, Apr 07, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Marijn ten Thij, Vrije Universiteit Amsterdam
Talk Title: Beyond tracking: modelling human behavior through social media
Abstract: In this talk, I present my ongoing work in modeling human behavior
using data from online platforms. I will discuss three of my projects
that focus on two online platforms Wikipedia and Twitter. First, I
will illustrate how I model the effect of promoting content on the
page view activity on Wikipedia by using the page view logs provided
by WikiMedia. I will then discuss the random graph model I designed
based on data from Twitter, which may be used to mimic the progression
of a trend through the network of Twitter. Finally, I will talk about
my current project, where we aim to capture business value from a
social feed for the Horticulture Industry.
Biography: Marijn ten Thij is a PhD student in Mathematics at Vrije Universiteit
Amsterdam, who graduated in Applied Mathematics at the Stochastic
Operations Research group at the University of Twente. His research
interest lies in the fields of Complex Science, Network Science and
Big Data. In 2014, Marijn was a member of the Dutch National
ThinkTank, where he worked on the question Can Big Data be used to
make the Netherlands more mobile, more social, and more healthy?
Marijn lives in Amsterdam and enjoys playing American pool billiards
in his spare time.
Host: Emilio Ferrara
More Info: http://webcastermshd.isi.edu/Mediasite/Play/d5714d851721421a857168a930b571e81d
Location: 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
Event Link: http://webcastermshd.isi.edu/Mediasite/Play/d5714d851721421a857168a930b571e81d
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Seminars in Biomedical Engineering
Fri, Apr 07, 2017 @ 02:30 PM - 04:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Raymond Goldsworthy, PhD, Associate Professor of Clinical Otolaryngology-Head and Neck Surgery
Talk Title: TBA
Series: Seminars in BME (Lab Rotations)
Biography: http://keck.usc.edu/faculty/raymond-l-goldsworthy/
Host: Brent Liu, PhD
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Apr 07, 2017 @ 02:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hua Wang, Assistant Professor, Georgia Institute of Technology
Talk Title: Pushing the Envelope of RF mmWave Power Generation by Relearning Ohms Law
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Hua Wang.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Apr 07, 2017 @ 03:00 PM - 04:00 PM
Conferences, Lectures, & Seminars
Speaker: Allyson McGaughey and Joao , TBA
Talk Title: TBA
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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NL Seminar - ConversAtion level Syntax SImilarity Metric CASSIM)
Fri, Apr 07, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Reihane Boghrati , (USC)
Talk Title: ConversAtion level Syntax SImilarity Metric CASSIM
Series: Natural Language Seminar
Abstract: Abstract: The syntax and semantics of human language can illuminate many individual psychological differences and important dimensions of social interaction. Thus, analysis of language provides important insights into the underlying psychological properties of individuals and groups. Accordingly, psychological and psycholinguistic research has begun incorporating sophisticated representations of semantic content to better understand the connection between word choice and psychological processes. While the majority of language analysis work in psychology has focused on semantics, psychological information is encoded not just in what people say, but how they say it. We introduce ConversAtion level Syntax SImilarity Metric (CASSIM), a novel method for calculating conversation-level syntax similarity. CASSIM estimates the syntax similarity between conversations by automatically generating syntactical representations of the sentences in conversations, estimating the structural differences between them, and calculating an optimized estimate of the conversation-level syntax similarity. Also, we conduct a series of analyses with CASSIM to investigate syntax accommodation in social media discourse. Further, building off of CASSIM, we propose ConversAtion level Syntax SImilarity Metric-Group Representations CASSIM GR. This extension builds generalized representations of syntactic structures of documents, thus allowing researchers to distinguish between people and groups based on syntactic differences.
Biography: Reihane is a forth year Ph.D student at USC, working with Morteza Dehghani in Computational Social Science Laboratory. She is interested in introducing new methods and computational models to psychology, and more broadly to social sciences. Her work spans the boundary between natural language processing and psychology, as does her intellectual curiosity.
Host: Marjan Ghazvininejad and Kevin Knight
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/
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Seminars in Biomedical Engineering
Mon, Apr 10, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Xiaoping Hu, PhD, UC Riverside
Talk Title: MRI with PET Imaging
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Emerging Trends Seminar Series
Mon, Apr 10, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: C.C. Jay Kuo, Dean's Professor of Electrical Engineering, Ming Hsieh Department of Electrical Engineering
Talk Title: CNN as Guided Multi-layer RECOS Transform
Series: Emerging Trends
Abstract: There is a resurging interest in developing a neural network based solution to supervised machine learning in the last 5 years. In this talk, I will provide a theoretical foundation to the working principle of the convolutional neural network (CNN) from a signal processing viewpoint. To begin with, the RECOS transform is introduced as a basic building block for CNNs.
The term RECOS is an acronym for REctified-COrrelations on a Sphere. It consists of two main concepts: data clustering on a sphere and rectification. Then, a CNN is interpreted as a network that implements the guided multilayer RECOS transform. Along this line, we first compare the traditional single-layer and modern multilayer signal analysis approaches. Then, we discuss how guidance is provided by data labels through back propagation in the training with an attempt to offer a smooth transition from weakly to heavily supervised learning. Finally, we show that a trained network can be greatly simplified in the testing stage, which demands only one bit representation for both filter weights and inputs. Several future research directions are pointed out at the end.
Biography: Dr. C.C. Jay Kuo received his Ph.D. degree from the Massachusetts Institute of Technology in 1987. He is now with the University of Southern California (USC) as Director of the Media Communications Laboratory and Dean's Professor in Electrical Engineering, Systems. His research interests are in the areas of digital media processing, compression, communication and networking technologies. Dr. Kuo was the Editor in Chief for the IEEE Trans. on Information Forensics and Security from 2012 through 2014. He was the Editor in Chief for the Journal of Visual Communication and Image Representation from 1997 through 2011, and served as Editor for 10 other international journals.
Dr. Kuo received the 1992 National Science Foundation Young Investigator (NYI) Award, the 1993 National Science Foundation Presidential Faculty Fellow (PFF) Award, the 2010 Electronic Imaging Scientist of the Year Award, the 2010-11 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, the 2011 Pan Wen Yuan Outstanding Research Award, the 2014 USC Northrop Grumman Excellence in Teaching Award, the 2016 USC Associates Award for Excellence in Teaching, the 2016 IEEE Computer Society Taylor L. Booth Education Award, the 2016 IEEE Circuits and Systems Society John Choma Education Award, the 2016 IS&T Raymond C. Bowman Award, and the 2017 IEEE Leon K. Kirchmayer Graduate Teaching Award. Dr. Kuo is a Fellow of AAAS, IEEE and SPIE. He has guided 140 students to their Ph.D. degrees and supervised 25 postdoctoral research fellows. Dr. Kuo is a co author of about 250 journal papers, 900 conference papers, 14 books and 30 patents.
Host: Ming Hsieh Institute
More Info: https://www.facebook.com/events/1444859602200671/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
Event Link: https://www.facebook.com/events/1444859602200671/
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Apr 10, 2017 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Natalie Cheung , Intel
Talk Title: Utilizing Drones to Create a New Nighttime Entertainment
Abstract: Come learn how Intel is utilizing drones in a different way -“ to light up the sky in a choreographed aerial performance with the Intel Drone Light Show. You'll learn about the Intel Shooting Star Drone, the technology behind the show, and more.
Biography: Natalie Cheung is the General Manager for the Drone Light Show in the UAV Group at Intel Corporation. She is responsible for establishing the drone light show business and growing the new segment. Cheung has led drone light show collaborations with customers that created activations across the globe - from the US, Germany, Mexico, Australia, and more.
Prior to her current role, Cheung was the Drone Marketing Director. She was responsible for product launches, conferences and events, and building awareness within the drone segment. Cheung has also served as Drone Product Manager, Research Analyst for Intel CEO Brian Krzanich. Cheung joined Intel in 2011. She earned a bachelor's and master's degree in electrical engineering and computer science from Massachusetts Institute of Technology.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
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USC Stem Cell Seminar: Ellen Rothenberg, California Institute of Technology
Tue, Apr 11, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Ellen Rothenberg, California Institute of Technology
Talk Title: TBD
Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series
Host: USC Stem Cell
More Info: http://stemcell.usc.edu/events
Webcast: http://keckmedia.usc.edu/stem-cell-seminarWebCast Link: http://keckmedia.usc.edu/stem-cell-seminar
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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Epstein Seminar, ISE 651
Tue, Apr 11, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ran Jin, Assistant Professor, Virginia Tech
Talk Title: Smart Manufacturing Modeling with Functional Data
Host: Prof. Qiang Huang
More Information: April 11, 2017_Jin.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Big Data & Human Behavior Seminar Series: Justin Grimmer (Stanford University) - Exploratory and Confirmatory Causal Inference for High Dimensional Interventions
Wed, Apr 12, 2017 @ 12:00 PM - 01:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Justin Grimmer, Associate Professor of Political Science and Computer Science, Stanford University
Talk Title: Exploratory and Confirmatory Causal Inference for High Dimensional Interventions
Series: Big Data & Human Behavior Seminar Series
Abstract: An extensive literature in computational social science examines how features of messages, advertisements, and other corpora affect individuals' decisions, but these analyses must specify the relevant features of the text before the experiment. Automated text analysis methods are able to discover features of text, but these methods cannot be used to obtain the estimates of causal effects-”the quantity of interest for applied researchers. We introduce a new experimental design and statistical model to simultaneously discover treatments in a corpora and estimate causal effects for these discovered treatments. We prove the conditions to identify the treatment effects of texts and introduce the supervised Indian Buffet process to discover those treatments. Our method enables us to discover treatments in a training set using a collection of texts and individuals' responses to those texts, and then estimate the effects of these interventions in a test set of new texts and survey respondents. We apply the model to an experiment about candidate biographies, recovering intuitive features of voters' decisions and revealing a penalty for lawyers and a bonus for military service.
Biography: Justin Grimmer's research examines how representation occurs in American politics using new statistical methods. His first book Representational Style in Congress: What Legislators Say and Why It Matters (Cambridge University Press, 2013) shows how senators define the type of representation they provide constituents and how this affects constituents' evaluations and won the Fenno Prize from the legislative studies section. His second book The Impression of Influence: How Legislator Communication and Government Spending Cultivate a Personal Vote (Princeton University Press, with Sean J. Westwood and Solomon Messing) demonstrates how legislators ensure they receive credit for government actions. His work has appeared in the American Political Science Review, American Journal of Political Science, Journal of Politics, Political Analysis, Proceedings of the National Academy of Sciences, Regulation and Governance, and other journals.
Host: Morteza Dehghani
Location: BCI
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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MHI CommNetS Seminar
Wed, Apr 12, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ian M. Mitchell, University of British Columbia
Talk Title: Using model checking verifications online: Handling runtime state uncertainty, human-in-the-loop shared control and sampled data feedback
Series: CommNetS
Abstract: Recent advances in model checking algorithms for continuous state systems allow us to demonstrate the existence of safe control policies robust to model error for cyber-physical systems (CPS) of practical interest, such as shared control drones or wheelchairs, or automated delivery of anesthesia. However, these verification results are only relevant if we can implement those policies. In this talk I will discuss investigations into three challenges that arise when it comes time to synthesize a feedback control signal that will keep the system safe: Online state uncertainty, human-in-the-loop shared control for older adults with cognitive impairment, and the sampled data nature of that feedback control in typical cyber-physical systems.
Biography: Ian M. Mitchell completed his doctoral work in engineering at Stanford University in 2002, spent a year as a postdoctoral researcher at the University of California at Berkeley, and is now an Associate Professor of Computer Science at the University of British Columbia. He is the author of the Toolbox of Level Set Methods, the first publicly available high accuracy implementation of solvers for dynamic implicit surfaces and the time dependent Hamilton-Jacobi equation that works in arbitrary dimension. His research interests include development of algorithms and software for nonlinear differential equations, formal verification, control and planning in cyber-physical and robotic systems, assistive technology and reproducible research.
Host: Prof. Insoon Yang
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Aerospace & Mechanical Engineering Seminar
Wed, Apr 12, 2017 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Jeff Eldredge, Professor, Mechanical & Aerospace Engineering Department, University of California at Los Angeles
Talk Title: Low-Order Modeling of Agile Flight
Abstract: The highly agile flight exhibited by many flying creatures has, for many years, been the promise for the next generation of flight vehicles. However, the reality still falls short, in part because such agility requires flight control strategies that work robustly in the regime of separated flows. This regime, generally avoided by human-engineered vehicles, is often exploited by airborne creatures in order to make rapid maneuvers or maintain tolerance to gusts. Recent control strategies based on flapping wings or managed separation over fixed wings have shown promise, but are limited to slow maneuvers because they rely on linearized and/or quasi-steady models of the aerodynamics, only effective at low frequencies or averaged over many flapping cycles. In this presentation, I will report on our recent progress in developing unsteady non-linear (vortex-based) models of separated flows. The premise is to construct a low-degree-of-freedom template model, with the simplest description of the flow that still contains the non-linear vortex-vortex and vortex-wing interactions. The model is then closed with empirical data from sensors. I will demonstrate progress on several canonical problems in two dimensions, and discuss our extensions to fully three-dimensional flows. I will also highlight some future directions of the work.
Biography: Jeff Eldredge is a Professor in the Mechanical & Aerospace Engineering Department at UCLA. His research interests are in computational and theoretical studies of problems in fluid dynamics, including those in unsteady aerodynamics, bio-inspired locomotion, micro-particle manipulation, and biomedical and physiological flows. He has received the NSF CAREER Award and is an Associate Fellow of AIAA. Prior to starting at UCLA, Prof. Eldredge was a research associate at the University of Cambridge. He received his M.S and Ph.D. at Caltech and his B.S. at Cornell, all in mechanical engineering.
Host: Department of Aerospace and Mechanical Engineering
More Info: https://ame.usc.edu/about/seminars/
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
Event Link: https://ame.usc.edu/about/seminars/
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Mork Family Department Graduate Seminar
Fri, Apr 14, 2017 @ 11:00 AM - 12:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dr. Morgan Trassin, Department of Materials, ETH Zurich, Switzerland.
Talk Title: Monitoring the emergence of polarization in ferroelectric oxide heterostructures
Host: Dr. Jayakanth Ravichandran
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Everyone Is Invited
Contact: Aleessa Atienza
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AI Seminar
Fri, Apr 14, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Wei Wang, UCLA
Talk Title: Big Data Analytics in Science
Abstract: Big data analytics is the process of examining large amounts of data of a variety of types (big data) to uncover hidden patterns, unknown correlations, and other useful information. Its revolutionary potential is now universally recognized. Data complexity, heterogeneity, scale, and timeliness make data analysis a clear bottleneck in many biomedical applications, due to the complexity of the patterns and lack of scalability of the underlying algorithms. Advanced machine learning and data mining algorithms are being developed to address one or more challenges listed above. It is typical that the complexity of potential patterns may grow exponentially with respect to the data complexity, and so is the size of the pattern space. To avoid an exhaustive search through the pattern space, machine learning and data mining algorithms usually employ a greedy approach to search for a local optimum in the solution space or use a branch-and-bound approach to seeking optimal solutions, and consequently, are often implemented as iterative or recursive procedures. To improve efficiency, these algorithms often exploit the dependencies between potential patterns to maximize in-memory computation and/or leverage special hardware for acceleration. These lead to strong data dependency, operation dependency, and hardware dependency, and sometimes ad hoc solutions that cannot be generalized to a broader scope. In this talk, I will present some open challenges faced by data scientist in biomedical fields and the current approaches taken to tackle these challenges.
Biography: California, Los Angeles and the director of the Scalable Analytics Institute (ScAi). She received her Ph.D. degree in Computer Science from the University of California, Los Angeles in 1999. She was a professor in Computer Science at the University of North Carolina at Chapel Hill from 2002 to 2012 and was a research staff member at the IBM T. J. Watson Research Center between 1999 and 2002. Dr. Wang's research interests include big data analytics, data mining, bioinformatics and computational biology, and databases. She has filed seven patents and has published one monograph and more than one hundred seventy research papers in international journals and major peer-reviewed conference proceedings.
Dr. Wang received the IBM Invention Achievement Awards in 2000 and 2001. She was the recipient of an NSF Faculty Early Career Development (CAREER) Award in 2005. She was named a Microsoft Research New Faculty Fellow in 2005. She was honored with the 2007 Phillip and Ruth Hettleman Prize for Artistic and Scholarly Achievement at UNC. She was recognized with an IEEE ICDM Outstanding Service Award in 2012, an Okawa Foundation Research Award in 2013, and an ACM SIGKDD Service Award in 2016. Dr. Wang has been an associate editor of the IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Big Data, ACM Transactions on Knowledge Discovery in Data, Journal of Knowledge and Information Systems, Data Mining and Knowledge Discovery, and International Journal of Knowledge Discovery in Bioinformatics. She serves on the organization and program committees of international conferences including ACM SIGMOD, ACM SIGKDD, ACM BCB, VLDB, ICDE, EDBT, ACM CIKM, IEEE ICDM, SIAM DM, SSDBM, RECOMB, BIBM. She was elected to the Board of Directors of the ACM Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics (SIGBio) in 2015.
Host: Mayank Kejriwal
More Info: http://webcastermshd.isi.edu/Mediasite/Play/6660ae1a19c74378b4e0db116f3413291d
Location: Information Science Institute (ISI) - 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
Event Link: http://webcastermshd.isi.edu/Mediasite/Play/6660ae1a19c74378b4e0db116f3413291d
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Jelena Vuckovic - Munushian Seminar, Friday, April 14th at 2:00pm in EEB 132
Fri, Apr 14, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jelena Vuckovic, Stanford University
Talk Title: Quantum Nanophotonics
Abstract: Nanophotonic structures that localize photons in sub-wavelength volumes are possible today thanks to modern nanofabrication and optical design techniques. Such structures enable studies of new regimes of light-matter interaction, quantum and nonlinear optics, and new applications in computing, communications, and sensing. While the traditional quantum nanophotonics platform is based on quantum dots inside photonic crystal cavities, recently a lot of progress has been made on systems consisting of color centers in diamond and silicon carbide, which could potentially bring these experiments to room temperature and facilitate scaling to large networks of resonators and emitters. Moreover, the use of inverse nanophotonic design methods, that can efficiently perform physics-guided search through the full parameter space, leads to optical devices with properties superior to state of the art, including smaller footprints, better field localization, and novel functionalities.
Biography: Jelena Vuckovic (PhD Caltech 2002) has been a faculty at Stanford since 2003, where she is currently a Professor of Electrical Engineering and by courtesy of Applied Physics, and where she leads the Nanoscale and Quantum Photonics Lab. She has also held visiting positions at the Humboldt University in Berlin, Germany, and the Technical University in Munich, Germany. Vuckovic is a recipient of numerous awards, including the Humboldt Prize, the Hans Fischer Senior Fellowship, and the Presidential Early Career Award for Scientists and Engineers (PECASE). She is a Fellow of the American Physical Society (APS) and of the Optical Society of America (OSA), and a member of the scientific advisory board of the Max Planck Institute for Quantum Optics (MPQ) in Munich, Germany.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Seminars in Biomedical Engineering
Fri, Apr 14, 2017 @ 02:30 PM - 04:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: NO SEMINAR DUE TO GRODINS SYMPOSIUM, NO SEMINAR DUE TO GRODINS SYMPOSIUM
Talk Title: NO SEMINAR DUE TO GRODINS SYMPOSIUM
Series: Seminars in BME (Lab Rotations)
Host: Brent Liu, PhD
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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NL Seminar- Why is it harder to build a tic tac toe playing robot than a tic tac toe playing program?
Fri, Apr 14, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kevin Knight, USC/ISI
Talk Title: Why is it harder to build a tic tac toe playing robot than a tic tac toe playing program?
Series: Natural Language Seminar
Abstract: I wanted to understand why it's so hard to build working robots, so I programmed one to play tic tac toe. Now I understand a lot better! I thought I'd relate my experience right now, just in case I later become more knowledgeable and impossible to understand.
Biography: Kevin Knight is a Research Director at the Information Sciences Institute ISI of the University of Southern California USC, and a Professor in the USC Computer Science Department. He received a PhD in computer science from Carnegie Mellon University and a bachelors degree from Harvard University. Dr. Knights research interests include statistical machine translation, natural language generation, automata theory, and decipherment of historical manuscripts.
Host: Marjan Ghazvininejad
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/
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Apr 14, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Yamrot Amha and Qian Feng, Astani CEE Graduate Students
Talk Title: Elucidating Microbial Community Adaptation to Anaerobic Co-digestion of Fats, Oils, and Grease and Food Waste and Optimal Clipped Linear Strategies for Controllable Damping
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Mork Family Department Graduate Seminar
Mon, Apr 17, 2017 @ 11:00 AM - 12:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Kedar Hippalgaonkar, Institute of Materials Research and Engineering, Agency for Science Technology and Research
Talk Title: Electron and Phonon Transport in 1D and 2D Materials Towards Applications in Thermoelectrics
Host: Dr. Jayakanth Ravichandran
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Department Only
Contact: Aleessa Atienza
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Seminars in Biomedical Engineering
Mon, Apr 17, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Rich Roberts, PhD, Dept. Chair, USC Chemical Engineering & Materials Science
Talk Title: 20 years of mRNA Display for Peptide and Protein Design
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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PTE Seminar
Mon, Apr 17, 2017 @ 12:50 PM - 01:50 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Rafael Moraes, Reservoir Simulation Engineer, Petrobras Research & Development Center
Talk Title: Improving the Computational Efficiency of Approximate Gradients Using a MultiScale Reservoir Simulation Framework
Host: Dr. Behnam Jafarpour
Location: Thomas & Dorothy Leavey Library (LVL) - 17
Audiences: Everyone Is Invited
Contact: Aleessa Atienza
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USC Stem Cell Seminar: Catriona Jamieson, University of California, San Diego
Tue, Apr 18, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Catriona Jamieson, University of California, San Diego
Talk Title: TBD
Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series
Host: USC Stem Cell
More Info: http://stemcell.usc.edu/events
Webcast: http://keckmedia.usc.edu/stem-cell-seminarWebCast Link: http://keckmedia.usc.edu/stem-cell-seminar
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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Epstein Seminar, ISE 651
Tue, Apr 18, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Mark Brown, Professor, Columbia University
Talk Title: Taylor's Law via Ratios, for Some Distributions with Infinite Mean
Host: Prof. Sheldon Ross
More Information: April 18, 2017_Brown.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Aerospace & Mechanical Engineering Seminar
Wed, Apr 19, 2017 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Ilenia Battiato, Assistant Professor of Energy Resources Engineering at Stanford University
Talk Title: Transport Phenomena over Patterned Surfaces
Abstract: Coupled flows over patterned surfaces occur in a variety of natural phenomena, biological systems and industrial processes. Some example includes bioreactors, micro- and nano-patterned water filtration membranes, superhydrophobic ridges surfaces, and submerged vegetation, just to mention a few. Designing and optimizing the topology of the structure to achieve target performance at the system-scale (or macroscale) is still an open question since fully resolved numerical simulations are too prohibitive when a great disparity of scales between the pattern and the device exists. By treating the patterned surface as a permeable layer, we formulate a system of coupled Navier-Stokes/Brinkman equations, which is amenable of analytical solution for the mean filtration velocity inside the pattern, and allows one to uncover and quantify the relationship between microstructure and macroscopic response. We employ this effective-medium framework to model a number of physical systems including channel turbulent flows over arrays of carbon nanotubes, superhydrophobic ridged surfaces, and submerged vegetation. We finally investigate the appropriateness of treating the pattern as a porous medium by conducting experiments in microfluidic channels with controlled microtexture.
Biography: Dr. Battiato received her MSc. In Engineering Physics in 2008 and a Ph.D. in Engineering Science with a specialization in Computational Sciences from the Mechanical and Aerospace Engineering department at the University of California San Diego in 2010. She did her postdoctoral training in Theoretical Physics at the Max Planck Institute for Dynamics and Self-Organization in Goettingen, Germany. In 2012 she joined the Mechanical Engineering Department at Clemson University as assistant professor and then in 2014 the Mechanical Engineering Department at SDSU. In 2016, she moved to the department of Energy Resources Engineering at Stanford University. Her research interests lie in theoretical/computational fluid mechanics and transport processes in porous media, multiscale and hybrid computational methods, effective medium theories, and multiphase flows. In 2015 she was awarded of the Department of Energy Young Investigator award in Basic Energy Sciences for her work on multiscale models of reactive transport in the subsurface.
Host: Department of Aerospace and Mechanical Engineering
More Info: https://ame.usc.edu/about/seminars/
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
Event Link: https://ame.usc.edu/about/seminars/
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CS Colloquium: Satish Chandra (Facebook) - Formula-Based Software Debugging
Thu, Apr 20, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Satish Chandra , Facebook
Talk Title: Formula-Based Software Debugging
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Software often ships with known defects because fixing bugs requires expensive developer time. With the availability of virtually unlimited compute power, an interesting question is whether the burden of fixing bugs can be shifted, at least in part, from the human to the machine. This question has, of late, attracted significant activity in the software engineering and programming language communities. In this talk, I will discuss recent techniques that have been proposed towards this goal. My main focus will be on techniques that draw on the power of SMT (satisfiability modulo theories) solvers, i.e. engines that crunch first-order logic formulae.
Time permitting, I will also talk about my experiences with tech transfer at industrial research labs.
Biography: Satish Chandra obtained a PhD from the University of Wisconsin-Madison in 1997, and a B.Tech from the Indian Institute of Technology-Kanpur in 1991, both in computer science. From 1997 to 2002, he was a member of technical staff at Bell Laboratories, where his research focused on program analysis, domain-specific languages, and data-communication protocols. From 2002 to 2013, he was a research staff member at IBM Research, where his research focused on bug finding and verification, software synthesis, and test automation.
From 2013 to 2016, he worked at Samsung Research America, where he led the advanced programming tools research team. In 2016, he started working at Facebook. He is an ACM Distinguished Scientist.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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AI Seminar
Fri, Apr 21, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Homa Hosseinmardi , Danaher Corporation
Talk Title: Multimodal Labeling and Characterization of Social Network Data for Detection/Prediction of Cyberbullying
Abstract: One of the most pressing problems in high schools is bullying. However, with todays online and mobile technologies, bullying is moving beyond the schoolyards via cell phones, social networks, online text, videos, and images. As bad as fighting and bullying were before the internet age, the recording and posting of hurtful content online have magnified the harmful reach of bullying, enabling it 24 7. Cyberbullying is a growing problem and incidents of cyberbullying with extreme consequences such as suicide are routinely reported in popular press now. This talk provides insights into the problem of cyberbullying in social networks by investigating profanity usage, ground truth labeling of cyberbullying, and characterization of relationships between cyberbullying and a variety of factors, including linguistic content, social graph features, temporal commenting behavior, and multimedia modality. It also looks at the propagation of cyberbullying behavior in a social network, and prediction of victims of such behavior.
Biography: Homa Hosseinmardi holds PhD in Computer Science from the University of Colorado Boulder. She joined Danaher Corporation in 2015 as Data Scientist at Danaher Labs. She also contributes as a researcher at the CU CyberSafety Research Center. Hosseinmardis interests lie in the area of computational social science and data mining. She is particularly interested in the use of large scale datasets and machine learning techniques to study problems with internet safety, misbehavior and cyberbullying. Her recent work has focused on studying triggers of cyberaggressive behaviors. Her past work also addressed various questions toward understanding cyberbullying in online social networks.
Host: Emilio Ferrara
Location: 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Apr 21, 2017 @ 02:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Aaron Buchwald, Senior Technical Director at InPhi Corporation
Talk Title: Challenges of Time-Interleaved ADCs
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Aaron Buchwald.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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Seminars in Biomedical Engineering
Fri, Apr 21, 2017 @ 02:30 PM - 04:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Leonard Morsut, PhD, Assistant Professor, Broad CIRM Center and Dept. of Stem Cell Biology and Regenerative Medicine University of Southern California Keck School of Medicine
Talk Title: Programming cells to build tissues with synthetic biology molecular tools: a new pathway towards engineering development and regeneration
Series: Seminars in BME (Lab Rotations)
Abstract: During embryonic development, complex multicellular tissues form based on genetically encoded algorithms that specify how cells will behave both individually and collectively.
In the Tissue Development Engineering Laboratory we develop synthetic biology approaches to implement in cells such self-organization programs and understand their overall logic, both for basic understanding and applications in regenerative medicine.
We have recently engineered and characterized a family of orthogonal cell-cell communication pathways, inspired by the mechanism of an endogenous communication system called Notch, which allows a cell to detect molecular signals from its neighbors and, in response, to induce user-specified transcriptional programs. These synthetic Notch pathways do not crosstalk with native pathways or with each other, thus providing multiple novel channels for engineering cell-cell communication. I will show how we used these synthetic pathways to flexibly construct basic routines for multi-cellular patterning and morphogenesis in mammalian cellular systems, e.g. localized differentiation, spatial patterning and Boolean decisions. Then, using the synthetic pathways in combination with adhesion molecules we designed a series of synthetic morphogenetic programs in 3D spheroids that deterministically drive spatial reorganization and symmetry breaking in a dynamic, self-organized fashion; we show that these trajectories are robust to perturbations and capable of self-regeneration. I will discuss possible applications of these technologies for developmental biology and regenerative medicine research and applications, especially in combination with tissue engineering tools and approaches. With the increasingly sophisticated synthetic biology components available today and the developments of tissue engineering we are going towards the possibility of designing the development of functional tissues in a dish with user-defined high level properties like shape, resistance to injury, regeneration, for the next generation of regenerative medicine applications.
Biography: http://morsutlab.usc.edu/
Host: Brent Liu, PhD
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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NL Seminar - REINFORCEMENT LEARNING OF NEGOTIATION DIALOGUE POLICIES
Fri, Apr 21, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kallirroi Georgila , USC/ICT
Talk Title: REINFORCEMENT LEARNING OF NEGOTIATION DIALOGUE POLICIES
Series: Natural Language Seminar
Abstract: The dialogue policy of a dialogue system decides on what dialogue move also called action, the system should make given the dialogue context also called dialogue state. Building hand crafted dialogue policies is a hard task, and there is no guarantee that the resulting policies will be optimal. This issue has motivated the dialogue community to use statistical methods for automatically learning dialogue policies, the most popular of which is reinforcement learning RL. However, to date, RL has mainly been used to learn dialogue policies in slot filling applications e.g. restaurant recommendation, flight reservation, etc. largely ignoring other more complex genres of dialogue such as negotiation. This talk presents challenges in reinforcement learning of negotiation dialogue policies. The first part of the talk focuses on applying RL to a two party multi issue negotiation domain. Here the main challenges are the very large state and action space, and learning negotiation dialogue policies that can perform well for a variety of negotiation settings, including against interlocutors whose behavior has not been observed before. Good negotiators try to adapt their behaviors based on their interlocutors' behaviors. However, current approaches to using RL for dialogue management assume that the users behavior does not change over time. In the second part of the talk, I will present an experiment that deals with this problem in a resource allocation negotiation scenario.
Biography: Kallirroi Georgila is a Research Assistant Professor at the Institute for Creative Technologies ICT at the University of Southern California US and at USCs Computer Science Department. Before joining USC ICT in 2009 she was a Research Scientist at the Educational Testing Service ETS and before that a Research Fellow at the School of Informatics at the University of Edinburgh. Her research interests include all aspects of spoken dialogue processing with a focus on reinforcement learning of dialogue policies, expressive conversational speech synthesis, and speech recognition. She has served on the organizing, senior, and program committees of many conferences and workshops. Her research work is funded by the National Science Foundation and the Army Research Office.
Host: Marjan Ghazvininejad and Kevin Knight
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/
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Seminars in Biomedical Engineering
Mon, Apr 24, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Arman Nadershahi, AMI, Sr. Director Corporate and Intellectual Property Counsel
Talk Title: Microbiology with Therapy
Biography: Mr. Nadershahi serves as Senior Director, Corporate and Intellectual Property Counsel. His expertise includes patent, trademark, and trade-secret protection and licensing; mergers and acquisitions; corporate law; raising capital for start-up companies; FDA regulatory affairs; quality assurance; competitive strategy and planning; product development; technology valuation and commercialization; and leadership.
Prior to joining AMI-USC, Mr. Nadershahi practiced intellectual property law at Knobbe, Martens, Olson & Bear, LLP, where he focused on patent prosecution, licensing, and intellectual property litigation in the fields of biotechnology, pharmaceuticals, and medical devices. Arman is also a co-founder and the CEO of Proa Medical, Inc., a spinout company from AMI-USC that commercializes medical devices for women's health.
Mr. Nadershahi is a member of the State Bar of California, is registered to practice before the United States Patent and Trademark Office, has earned US and EU Regulatory Affairs Certification (RAC-US & RAC-EU), is an ASQ Certified Biomedical Auditor (CBA), and is an ASQ Certified Manager of Quality/Organization Excellence (CMQ/OE).
Mr. Nadershahi graduated with distinction from the University of Wisconsin-Madison with a Bachelor of Arts degree in Zoology and English Literature. He received a Juris Doctor from the University of Minnesota Law School, a Master of Science degree in Biological Science from the University of Minnesota, a Master of Science degree in Regulatory Science from the University of Southern California (USC) School of Pharmacy, and a Master of Business Administration degree from the Marshall School of Business at USC.
Mr. Nadershahi may be contacted at nadersha AT usc DOT edu.
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems
Mon, Apr 24, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dennice F. Gayme, Assistant Professor, Johns Hopkins University
Talk Title: Quantifying efficiency and robustness in large-scale networks
Abstract: Dynamical systems coupled over graphs arise in a number of applications from power grids to vehicle networks. These systems are most often characterized in terms of their stability. However, the performance of these networks is also of great importance as it often corresponds to system efficiency and robustness. In this talk, we discuss a broad class of performance measures for first and second order systems whose outputs are defined so that particular performance metrics can be quantified through the input-output H2 norm of the system. We first present results for systems with the same physical interconnection and communication graph structures. We discuss the effect of graph size and interconnection structure for two applications; characterizing transient real power losses in power grids and evaluating long range disorder in vehicular platoons with both relative and absolute velocity feedback. We then extend our results to vehicular networks with arbitrary physical arrangements and communication structures to demonstrate that our proposed suite of performance measures can be adapted to determine the minimum disturbance energy that is required to cause a collision between any two vehicles. Finally, we further explore the effect of graph structure by considering systems with directed communication graphs.
Biography: Dennice F. Gayme is an Assistant Professor and the Carol Croft Linde Faculty Scholar in Mechanical Engineering at the Johns Hopkins University. She earned her B. Eng. & Society from McMaster University in 1997 and an M.S. from the University of California at Berkeley in 1998, both in Mechanical Engineering. She received her Ph.D. in Control and Dynamical Systems in 2010 from the California Institute of Technology, where she was a recipient of the P.E.O. scholar award in 2007 and the James Irvine Foundation Graduate Fellowship in 2003. Her research interests are in modeling, analysis and control for spatially distributed and large-scale networked systems in applications such as wall-bounded turbulent flows, wind farms, power grids and vehicular networks. She was a recipient of the JHU Catalyst Award in 2015, a 2017 ONR Young Investigator award, and an NSF CAREER award in 2017.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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CS Colloquium Event: Facebook Tech Talk - Query Understanding and Semantic Search
Mon, Apr 24, 2017 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Haixun Wang, Facebook
Talk Title: Facebook Tech Talk - Query Understanding and Semantic Search
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Research Colloquium.
Understanding short texts is crucial to many applications, but challenges abound. First, queries do not always observe the syntax of a written language. As a result, traditional natural language processing methods cannot be easily applied. Second, queries usually do not contact in sufficient statistical signals to support many state-of-the-art approaches for text processing such as topic modeling. Third, queries are usually more ambiguous. We argue that knowledge is needed in order to better understand short texts. In this talk, I describe how to use lexical semantic knowledge provided by a well-known semantic network for short text understanding. Our knowledge-intensive approach disrupts traditional methods for tasks such as text segmentation, part-of-speech tagging, and concept labeling, in the sense that we focus on semantics in all the set tasks. We conduct a comprehensive performance evaluation on real-life data. The results show that knowledge is indispensable for short text understanding, and our knowledge-intensive approaches are effective in harvesting semantics of short texts.
Biography: Haixun Wang is a Research Scientist at Facebook and he manages the Query and Document Understanding team. Before Facebook, he was with Google Research, working on natural language processing. From 2009 to 2013, he led research in semantic search, graph data processing systems, and distributed query processing at Microsoft Research Asia. He had been a research staff member at IBM T. J. Watson Research Center from 2000 -“ 2009. He was Technical Assistant to Stuart Feldman (Vice President of Computer Science of IBM Research) from 2006 to 2007, and Technical Assistant to Mark Wegman (Head of Computer Science of IBM Research) from 2007 to 2009. He received the Ph.D. degree in Computer Science from the University of California, Los Angeles in 2000. He has published more than 150 research papers in referred international journals and conference proceedings. He served PC Chair of conferences such as CIKM'12, and he is on the editorial board of journals such as IEEE Transactions of Knowledge and Data Engineering (TKDE) and Journal of Computer Science and Technology (JCST). He won the best paper award in ICDE 2015, 10 year best paper award in ICDM 2013, and best paper award of ER 2009.
Host: CS Department
Location: Mark Taper Hall Of Humanities (THH) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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USC Stem Cell Seminar: Maurizio Pacifici, The Children's Hospital of Philadelphia
Tue, Apr 25, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Maurizio Pacifici, The Children's Hospital of Philadelphia
Talk Title: TBD
Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series
Host: USC Stem Cell
More Info: http://stemcell.usc.edu/events
Webcast: http://keckmedia.usc.edu/stem-cell-seminarWebCast Link: http://keckmedia.usc.edu/stem-cell-seminar
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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CommNetS seminar
Tue, Apr 25, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Christian Grussler, Lund University
Talk Title: Low-Rank Inducing Norms with Optimality Interpretations
Series: CommNetS
Abstract: This talk is on optimization problems which are convex apart from a sparsity/rank constraint. These problems are often found in the context of compressed sensing, linear regression, matrix completion, low-rank approximation and many more. Today, one of the most widely used methods for solving these problems is so-called nuclear norm regularization. Despite the nice probabilistic guarantees of this method, this approach often fails for problems with structural constraints.
In this talk, we will present an alternative by introducing the family of so-called low-rank inducing norms as convexifiers. Each norm is the convex envelope of a unitarily invariant norm plus a rank constraint. Therefore, they have several interesting properties, which will be discussed throughout the talk. They:
i) Give a simple deterministic test if the solution to the convexified problem is a solution to a specific non-convex problem.
ii) Often finds solutions where the nuclear norm fails to give low-rank solutions.
iii) Allow us to analyze the convergence of non-convex proximal splitting algorithms with convex analysis tools.
iv) Provide a more efficient regularization than the traditional scalar multiplication of the nuclear norm.
v) Leads to a different interpretation of the nuclear norm than the one that is traditionally presented.
vi) In particular, all the results can be generalized to so-called atomic norms.
Biography: Christian Grussler is a postdoc at the Department of Automatic Control at Lund University, Sweden. His current research interests include positive systems, model reduction, system identification and low-rank/sparse optimization. He received a Dipl.-Math. techn. degree (Industrial Mathematics) from TU Kaiserslautern, Germany and an M.Sc. degree (Engineering Mathematics) from Lund University in 2011. In 2017, he received a Ph.D. degree from Lund University under the guidance of Anders Rantzer and Pontus Giselsson.
Host: Prof. Mihailo Jovanovic
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Annie Yu
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Epstein Seminar, ISE 651
Tue, Apr 25, 2017 @ 03:00 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Alper Atamturk, Professor, UC Berkeley
Talk Title: Combinatorial Optimization with a Probabilistic Objective
Host: Prof. Suvrajeet Sen
More Information: April 25, 2017_Atamturk.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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MHI Emerging Trends Seminar Series
Wed, Apr 26, 2017 @ 10:00 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kai Hwang, Professor, Ming Hsieh Department of Electrical Engineering
Talk Title: Big-Data Analytics for Cloud Computing in Cognitive Applications
Series: Emerging Trends
Abstract: In this talk, Dr. Hwang will address the effective use of big-data analytics on smart clouds, social networks, intelligent robots, and IoT platforms. He will assess machine/deep learning models and available software tools to advance the cognitive service industry represented by Google, Microsoft, Apple, Facebook, Baidu, IBM, Huawei, etc. The ultimate goal is to achieve enhanced agility, mobility, security, and scalability of public clouds, IoT platforms, and social-media networks.
His talk will assess current AI programs and brain projects pursued by high-tech companies, including Google X-Lab, TensorFlow, DeepMind AlphaGo, Nvidia Digits 5 for using GPU in deep learning, IBM neuromorphic computer, and CAS/ICT Camericon project, etc. Some hidden R/D opportunities are revealed for building smart machinesï¼delivery drones, self-driving cars, blockchains, AR/VR gears, etc. Extended cognitive applications will be discussed for 5G health-care, desease detection, emotion control, and social media community services.
Biography: Kai Hwang is a Professor of EE/CS at the Univ. of Southern California. He received the Ph.D. from UC Berkeley. He has published extensively in computer architecture, parallel processing, cloud computing, and network security. His latest two books are entitled: Cloud Computing for Machine Learning and Cognitive Applications (The MIT Press, April 2017) and Big Data Analytics for Cloud/IoT and Cognitive Computing (Wiley, U.K, May 2017).
An IEEE Life Fellow, he received the very-first CFC Outstanding Achievement Award in 2004 and the Lifetime Achievement Award from IEEE Cloud2012 for his pioneering work in parallel computing and distributed systems. Four of his graduated Ph.D. students were elected as IEEE Fellows and one an IBM Fellow. He has delivered four dozens of keynote or distinguished lectures in international Conferences or Research Centers. Dr. Hwang has performed consulting work with IBM, MIT Lincoln Lab, Chinese Academy of Sciences, and INRIA in France. He can be reached via his Email at USC: kaihwang@usc.edu.
Host: Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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MHI Emerging Trends Seminar Series
Wed, Apr 26, 2017 @ 10:00 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kai Hwang, Professor, Ming Hsieh Department of Electrical Engineering
Talk Title: Big-Data Analytics for Cloud Computing in Cognitive Applications
Series: Emerging Trends
Abstract: In this talk, Dr. Hwang will address the effective use of big-data analytics on smart clouds, social networks, intelligent robots, and IoT platforms. He will assess machine/deep learning models and available software tools to advance the cognitive service industry represented by Google, Microsoft, Apple, Facebook, Baidu, IBM, Huawei, etc. The ultimate goal is to achieve enhanced agility, mobility, security, and scalability of public clouds, IoT platforms, and social-media networks.
His talk will assess current AI programs and brain projects pursued by high-tech companies, including Google X-Lab, TensorFlow, DeepMind AlphaGo, Nvidia Digits 5 for using GPU in deep learning, IBM neuromorphic computer, and CAS/ICT Camericon project, etc. Some hidden R/D opportunities are revealed for building smart machines, delivery drones, self-driving cars, blockchains, AR/VR gears, etc. Extended cognitive applications will be discussed for 5G health-care, disease detection, emotion control, and social media community services.
Biography: Kai Hwang is a Professor of EE/CS at the Univ. of Southern California. He received his Ph.D. from UC Berkeley. He has published extensively in computer architecture, parallel processing, cloud computing, and network security. His latest two books are entitled: Cloud Computing for Machine Learning and Cognitive Applications (The MIT Press, April 2017) and Big Data Analytics for Cloud/IoT and Cognitive Computing (Wiley, U.K, May 2017).
An IEEE Life Fellow, he received the very first CFC Outstanding Achievement Award in 2004 and the Lifetime Achievement Award from IEEE Cloud2012 for his pioneering work in parallel computing and distributed systems. Four of his graduated Ph.D. students were elected as IEEE Fellows and one an IBM Fellow. He has delivered dozens of keynote or distinguished lectures in international Conferences or Research Centers. Dr. Hwang has performed consulting work with IBM, MIT Lincoln Lab, the Chinese Academy of Sciences, and INRIA in France. He can be reached via his Email at USC: kaihwang@usc.edu
Host: Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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Aerospace & Mechanical Engineering Laufer Lecture
Wed, Apr 26, 2017 @ 12:00 PM - 02:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Clarence W. Rowley, Professor, Department of Mechanical and Aerospace Engineering, Princeton University
Talk Title: Structure, Stability, and Simplicity in Complex Fluid Flows
Series: John Laufer Keynote Lecture Series
Abstract: Fluid flows can be extraordinarily complex, and even turbulent, yet often there is structure lying within the apparent complexity. Understanding this structure can help explain observed physical phenomena, and can help with the design of control strategies in situations where one would like to change the natural state of a flow. This talk addresses techniques for obtaining simple, approximate models for fluid flows, using data from simulations or experiments. We discuss a number of methods, including balanced truncation, linear stability theory, and dynamic mode decomposition, and apply them to several flows with complex behavior, including a transitional channel flow, a jet in crossflow, and a T-junction in a pipe.
Biography: Clancy Rowley is a Professor in the Mechanical and Aerospace Engineering department at Princeton University. He received his undergraduate degree from Princeton in 1995, and his doctoral degree from Caltech in 2001, both in Mechanical Engineering. He returned to Princeton in 2001 as an Assistant Professor and was appointed Associate Professor in 2007, and Full Professor in 2012. He has received several awards, including an NSF CAREER Award and an AFOSR Young Investigator Award. His research interests lie at the intersection of dynamical systems, control theory, and fluid mechanics, and focus on reduced-order models suitable for analysis and control design.
Host: Department of Aerospace and Mechanical Engineering
More Info: https://ame.usc.edu/about/seminars/
Location: Ronald Tutor Campus Center (TCC) - Trojan Ballroom A
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
Event Link: https://ame.usc.edu/about/seminars/
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MHI CommNetS seminar
Wed, Apr 26, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Adam Wierman, Caltech
Talk Title: Platforms & Networked Markets: Transparency & Market Power
Series: CommNetS
Abstract: Platforms have emerged as a powerful economic force, driving both traditional markets, like the electricity market, and emerging markets, like the sharing economy. The power of platforms comes from their ability to tame the complexities of networked marketplaces -- marketplaces where there is not a single centralized market, but instead a network of interconnected markets loosely defined by a graph of feasible exchanges. Despite the power and prominence of platforms, the workings of platforms are often guarded secrets, e.g., we know little about how amazon matches buyers and seller and how uber matches drivers and riders. Further, many competing platforms make very different design choices, but little is understood about the impact of these differing choices. In this talk, I will overview recent work that focuses on reverse engineering the design of platforms and understanding the consequences of design choices underlying modern platforms. I will use electricity markets and ridesharing services as motivating examples throughout the talk.
Biography: Adam Wierman is a Professor in the Department of Computing and Mathematical Sciences at the California Institute of Technology, where he currently serves as Executive Officer. He is also the director of the Information Science and Technology (IST) initiative at Caltech. He is the founding director of the Rigorous Systems Research Group (RSRG) and co-Director of the Social and Information Sciences Laboratory (SISL). His research interests center around resource allocation and scheduling decisions in computer systems and services. He received the 2011 ACM SIGMETRICS Rising Star award, the 2014 IEEE Communications Society William R. Bennett Prize, and has been coauthor on papers that received of best paper awards at ACM SIGMETRICS, IEEE INFOCOM, IFIP Performance (twice), IEEE Green Computing Conference, IEEE Power & Energy Society General Meeting, and ACM GREENMETRICS. Additionally, he maintains a popular blog called Rigor + Relevance.
Host: Prof. Insoon Yang
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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CS Colloquium and RASC seminar: Steven Waslander (University of Waterloo) - Gimballed multi-camera localization and mapping for aerial vehicles
Thu, Apr 27, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Steven Waslander, University of Waterloo
Talk Title: Gimballed multi-camera localization and mapping for aerial vehicles
Series: RASC Seminar Series
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Multi-camera clusters used for visual SLAM assume a fixed calibration between the cameras, which places many limitations on its performance, and directly excludes all configurations where a camera in the cluster is mounted to a moving component. We present a calibration method and SLAM solution for dynamic multi-camera clusters, where one or more of the cluster cameras is mounted to an actuated mechanism, such as a gimbal or robotic manipulator. Our approach parametrizes the actuated mechanism using the Denavit-Hartenberg convention, then determines the calibration parameters which allow for the estimation of the time varying extrinsic transformations between camera frames. We rely on joint encoder data or camera-attached IMU to identify the extrinsic transformations during operation, and are developing active calibration methods to automate the process in the field. We validate our calibration approach using a dynamic camera cluster consisting of a static camera and a camera mounted to a pan-tilt unit as well as on a four-camera system with a single three-axis gimballed unit on a hexacopter aerial vehicle, and demonstrate that dynamic camera clusters can be provide accurate pose tracking when used to perform SLAM.
Biography: Prof. Steven Waslander is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo in Waterloo, Ontario, Canada and director of the Waterloo Autonomous Vehicles Laboratory (WAVELab, http://wavelab.uwaterloo.ca). He received his B.Sc.E.in 1998 from Queen's University, his M.S. in 2002 and his Ph.D. in 2007, both from Stanford University in Aeronautics and Astronautics. He is the Program Co-Chair for the CIPPRS Computer and Robot Vision Conference, the Competition Chair for the IEEE/RSJ International Conference on Intelligent Robots and Systems and the former General Chair of the International Autonomous Robot Racing competition. His research interests lie in the areas of autonomous aerial and ground vehicles, autonomous driving, simultaneous localization and mapping, quadrotor vehicles, and machine learning. Prof. Waslander currently collaborates with numerous industrial partners, including Aeryon Labs, Clearpath Robotics, Nuvation Engineering, Denso, Renesas Electronics Corp, Qnx, and Applanix, and is a member of the NSERC Canadian Field Robotics Network. He also acts as the academic advisor to the University of Waterloo Robotics Team, which compete in multiple competitions, including the NASA Sample Return Robot Challenge, the Intelligent Ground Vehicle Competition and the University Rover Challenge.
Host: Gaurav Sukhatme
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Measurement and Analysis of Mobile and Social Networks
Thu, Apr 27, 2017 @ 11:00 AM - 12:15 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Athina Markopoulou, Professor/UC Irvine
Talk Title: Measurement and Analysis of Mobile and Social Networks
Abstract: The majority of Internet traffic today is through mobile devices and social media. Large-scale measurement and analysis of these systems is necessary in order to understand underlying patterns and enable engineering optimizations and new applications. In this talk, I will present highlights of our research in this area.
First, I will discuss online social networks. I will present our "2K+" framework for generating synthetic graphs that resemble online social networks, in terms of joint degree distribution and additional characteristics, such as clustering and node attributes [INFOCOM'13, INFOCOM'15]. This problem was motivated by our prior work on graph sampling [JSAC'11, SIGMETRICS'11, INFOCOM'10] and by popular demand to make the Facebook datasets we collected publicly available.
Second, I will discuss cellular networks. I will present our work on analyzing Call Detail Records (CDRs) in order to characterize human activity in urban environments, with applications to urban ecology [MOBIHOC'15] and ride-sharing [UBICOMP'14, SIGSPATIAL'15-16].
Third, I will present our ongoing work on AntMonitor - a system for monitoring network traffic on mobile devices [SIGCOMM C2BID'15], with applications to privacy leaks detection [MOBICOM Demo'15], crowdsourcing of network performance measurements, and improved wireless access.
Biography: Athina Markopoulou is an Associate Professor in EECS at the University of California, Irvine. She received the Diploma degree in Electrical and Computer Engineering from the National Technical University of Athens, Greece, in 1996, and the Master's and Ph.D. degrees in Electrical Engineering from Stanford University, in 1998 and 2003, respectively. She has held short-term/visiting appointments at SprintLabs (2003), Arista Networks (2005), IT University of Copenhagen (2012-2013), and she co-founded Shoelace Wireless (2012). She has received the NSF CAREER Award (2008), the Henry Samueli School of Engineering Faculty Midcareer Award for Research (2014), and the OCEC Educator Award (2017). She has been an Associate Editor for IEEE/ACM Transactions on Networking (2013-2015), an Associate Editor for ACM CCR (2016), the General Co-Chair for ACM CoNEXT 2016, and the Director of the Networked Systems program at UCI. Her research interests are in the area of networking including mobile systems and mobile data analytics, network measurement, online social networks, network security and privacy, network coding, and multimedia traffic.
Host: Professor Konstantinos Psounis, kpsounis@usc.edu
More Information: Seminar Announcement - Markopoulou 042717.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Le Val Lund Lecture with Student Symposium
Thu, Apr 27, 2017 @ 01:00 PM - 09:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Craig Davis, Technical Speaker and Recipient of the 2016 ASCE Le Val Lund Award for Practicing Lifeline Risk Reduction
Talk Title: Operationalizing Resilience for Lifeline Systems
Host: ASCE
More Information: Final_LeVal Lund_Lecture_save_the_date_v4_27April17.pdf
Location: California Institute of Technology
Audiences: Everyone Is Invited
Contact: Kaela Berry
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PhD Defense
Thu, Apr 27, 2017 @ 01:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Akshay Gadde, University of Southern California
Talk Title: Sampling and Filtering of Signals on Graphs with Applications to Active Learning and Image Processing
Abstract: Processing of signals defined over the nodes of a graph has generated a lot of interest recently. This is due to the emergence of modern application domains such as social networks, web information analysis, sensor networks and machine learning, in which graphs provide a natural representation for the data. Traditional data such as images and videos can also be represented as signals on graphs. A frequency domain representation for graph signals can be obtained using the eigenvectors and eigenvalues of operators which measure the variation in signals taking into account the underlying connectivity in the graph. Spectral filtering can then be defined in this frequency domain. Based on this, we develop a sampling theory for graph signals by answering the following questions: 1. When can we uniquely and stably reconstruct a bandlimited graph signal from its samples on a subset of the nodes? 2. What is the best subset of nodes for sampling a signal so that the resulting bandlimited reconstruction is most stable? 3. How to compute a bandlimited reconstruction efficiently from a subset of samples? The algorithms developed for sampling set selection and reconstruction do not require explicit eigenvalue decomposition of the variation operator and admit efficient, localized implementation. Using graph sampling theory, we propose effective graph based active semi-supervised learning techniques. We also give a probabilistic interpretation for the proposed techniques. Based on this interpretation, we generalize the framework of active learning on graphs using Bayesian methods to give an adaptive sampling method. Additionally, we study the application graph spectral filtering in image processing by representing the image as a graph, where the nodes correspond to the pixels and edge weights capture the similarity between them given by the coefficients of the bilateral filter. We show that the bilateral filter is a low pass graph spectral filter with linearly decaying spectral response. We then generalize the bilateral filter by defining filters on the above graph with different spectral responses depending on the application. We also consider the problem of constructing a sparse graph from the given data efficiently, which can be used in graph based learning and fast image adaptive filtering.
Biography: Akshay Gadde received his Bachelor of Technology degree in Electrical Engineering from Indian Institute of Technology (IIT), Kharagpur, India in 2011. He has been working towards a Ph.D. in Electrical Engineering at the University of Southern California (USC), Los Angeles since 2011. His work (with Prof. Antonio Ortega and Aamir Anis) won the Best Student Paper Award at ICASSP 2014. His research interests include graph signal processing and machine learning with applications to multimedia data processing and compression.
Host: Dr. Antonio Ortega
More Information: Gadde Seminar Announcement.png
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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Computer Architectures for Deep Learning Applications
Thu, Apr 27, 2017 @ 03:30 PM - 05:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: David Brooks, Harvard University
Talk Title: Computer Architectures for Deep Learning Applications
Abstract: Deep learning has been popularized by its recent successes on challenging artificial intelligence problems. One of the reasons for its dominance is also an ongoing challenge: the need for immense amounts of computational power. Hardware architects have responded by proposing a wide array of promising ideas, but to date, the majority of the work has focused on specific algorithms in somewhat narrow application domains. While their specificity does not diminish these approaches, there is a clear need for more flexible solutions. We believe the first step is to examine the characteristics of cutting edge models from across the deep learning community. Consequently, we have assembled Fathom: a collection of eight archetypal deep learning workloads for study. Each of these models comes from a seminal work in the deep learning community, ranging from the familiar deep convolutional neural network of Krizhevsky et al., to the more exotic memory networks from Facebook's AI research group. Fathom has been released online, and this talk describes the fundamental performance characteristics of each model. We use a set of application-level modeling tools built around the TensorFlow deep learning framework in order to analyze the behavior of the Fathom workloads. We present a breakdown of where time is spent, the similarities between the performance profiles of our models, an analysis of behavior in inference and training, and the effects of parallelism on scaling. The talk will then consider novel computer architectures that can improve the performance and efficiency of deep learning workloads.
Biography: David Brooks is the Haley Family Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University. Prior to joining Harvard, he was a research staff member at IBM T.J. Watson Research Center. Prof. Brooks received his BS in Electrical Engineering at the University of Southern California and MA and PhD degrees in Electrical Engineering at Princeton University. His research interests include resilient and power-efficient computer hardware and software design for high-performance and embedded systems. Prof. Brooks is a Fellow of the IEEE and has received several honors and awards including the ACM Maurice Wilkes Award, ISCA Influential Paper Award, NSF CAREER award, IBM Faculty Partnership Award, and DARPA Young Faculty Award.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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CS & ML Colloquium: Matus Telgarsky (UIUC) - Representation power of neural networks
Thu, Apr 27, 2017 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Matus Telgarsky, UIUC
Talk Title: Representation power of neural networks
Series: Yahoo! Labs Machine Learning Seminar Series
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
This talk will present a series of mathematical vignettes on the representation power of neural networks. Amongst old results, the classical universal approximation theorem will be presented, along with Kolmogorov's superposition theorem. Recent results will include depth hierarchies (for any choice of depth, there exists functions which can only be approximated by slightly less deep networks when they have exponential size), connections to polynomials (namely, rational functions and neural networks well-approximate each other), and the power of recurrent networks. Open problems will be sprinkled throughout.
Biography: Matus Telgarsky is an assistant professor at UIUC. He received his PhD in 2013 at UCSD under Sanjoy Dasgupta. He works in machine learning theory; his current interests are non-convex optimization and neural network representation.
Host: CS Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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AI Seminar
Fri, Apr 28, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Avi Pfeffer, Charles River Analytics
Talk Title: PROGRAMMING: PAST, PRESENT, AND FUTURE
Abstract: Probabilistic reasoning lets you predict the future, infer past causes of current observations, and learn from experience. It can be hard to implement a probabilistic application because you have to implement the representation, inference, and learning algorithms. Probabilistic programming makes this much easier by providing an expressive language to represent models as well as inference and learning algorithms that automatically apply to models written in the language. In this talk, I will present the past, present, and future of probabilistic programming and our Figaro probabilistic programming system. I will start with the motivation for probabilistic programming and Figaro. After presenting some basic Figaro concepts, I will introduce several applications we have been developing at Charles River Analytics using Figaro. Finally, I will describe our future vision of providing a probabilistic programming tool that domain experts with no machine learning knowledge can use. In particular, I will present a new inference method that is designed to work well on a wide variety of problems with no user configuration. Prior knowledge of machine learning is not required to follow the talk.
Biography: Dr. Avi Pfeffer is Chief Scientist at Charles River Analytics. Dr. Pfeffer is a leading researcher on a variety of computational intelligence techniques including probabilistic reasoning, machine learning, and computational game theory. Dr. Pfeffer has developed numerous innovative probabilistic representation and reasoning frameworks, such as probabilistic programming, which enables the development of probabilistic models using the full power of programming languages, and statistical relational learning, which provides the ability to combine probabilistic and relational reasoning. He is the lead developer of Charles River Analytics Figaro probabilistic programming language. As an Associate Professor at Harvard, he developed IBAL, the first general-purpose probabilistic programming language. While at Harvard, he also produced systems for representing, reasoning about, and learning the beliefs, preferences, and decision making strategies of people in strategic situations. Prior to joining Harvard, he invented object-oriented Bayesian networks and probabilistic relational models, which form the foundation of the field of statistical relational learning. Dr. Pfeffer serves as Action Editor of the Journal of Machine Learning Research and served as Associate Editor of Artificial Intelligence Journal and as Program Chair of the Conference on Uncertainty in Artificial Intelligence. He has published many journals and conference articles and is the author of a text on probabilistic programming. Dr. Pfeffer received his Ph.D. in computer science from Stanford University and his B.A. in computer science from the University of California, Berkeley.
Host: Craig Knoblock
More Info: http://webcastermshd.isi.edu/Mediasite/Play/9b1644b4150f48cabdccf208f55773a51d
Location: 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
Event Link: http://webcastermshd.isi.edu/Mediasite/Play/9b1644b4150f48cabdccf208f55773a51d
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Seminars in Biomedical Engineering
Fri, Apr 28, 2017 @ 02:00 PM - 04:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Samir Mitragotri , Mellichamp Chair Professor in the Department of Chemical Engineering at UC Santa Barbara
Talk Title: TBA
Series: Systems Cellular-Molecular Bioengineering Distinguished Speaker Series
Abstract: TBA
Biography: Professor Mitragotri is the Founding Director of Center for BioEngineering (CBE). CBE is a hub for research and teaching at the interface of biology, engineering and physical sciences and enables transition of fundamental scientific discoveries to applications in medicine and biotechnology. Research at the CBE is yielding important advances in the understanding, diagnosis and treatment of common and devastating diseases such as cancer, diabetes, Alzheimer's and macular degeneration.
Host: Eun Ji Chung, PhD
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Apr 28, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Calogero Benedetto Rizzo and Mohammed Abdelbarr, Astani CEE Graduate Students
Talk Title: A Systematic Investigation of Hydraulic Connectivity in Heterogeneous Porous Media and its Impact on Transport Dynamics
Abstract: Defining the level of connectivity of heterogeneous porous media is of key importance to understand subsurface flow and transport dynamics. Several studies show that non-Fickian behavior observed in solute spreading in heterogeneous subsurface formations are strictly related to the presence of preferential channels. The presence of these channels control the trajectory of the solute front leading edge of the plume and it is highly correlated to early arrival times. Nevertheless there are multiple metric and frameworks that allow to determine preferential channels and connectivity properties of a complex heterogeneous permeability field. The aim of this work is to understand connectivity properties by using the concept of least resistance path through the use of an efficient algorithm. We explore differences among a range of fields and analyze the factors that significantly affect the connectivity of the field and its impact on transport. The results help to further understand the impact of hydraulic connectivity on solute transport and to establish a criteria for which heterogeneity and preferential channels cannot be neglected.
Talk by Mohamed Abdelbarr
Title: Inexpensive and Contactless Color and Depth Data Fusion for Dynamic Displacement-Field Measurement
Abstract:
Quantitative and accurate measurements concerning the time history of the multi-component deformation field of a distributed system undergoing dynamic response is an important and challenging problem in the broad field of structural dynamics. There are only very limited, and relatively quite expensive, methodologies for obtaining multi component deformations of a displacement of a dynamically deformation field. This study presents an extensive analytical and experimental study to assess, implement, and evaluate the feasibility and performance of a class of inexpensive vision based sensors RGB-D sensors to acquire dynamic measurements of the displacement field of a test structure.
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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NL Seminar-Modeling Dialog using Probabilistic Programs
Fri, Apr 28, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Andreas Stuhlmuller , Stanford Univ.
Talk Title: Modeling Dialog Using Probabilistic Programs
Series: Natural Language Seminar
Abstract: How can we effectively explore the space of automated dialog systems? In this talk, I introduce WebPPL, a probabilistic programming language that provides a wide range of inference and optimization algorithms out of the box. This language makes it easy to express and combine probabilistic models, including regression and categorization models, highly structured cognitive models, models of agents that make sequential plans, and deep neural nets. I show that this also includes recent sequence to sequence architectures for dialog. I then use this framework to implement *dialog automation using workspaces, a variation on these architectures that is aimed at dialogs that require sufficiently deep reasoning between utterances that it is difficult to learn how to automate them from transcripts alone.
Biography: Andreas Stuhlmüller is a post-doctoral researcher at Stanford, working in Prof. Noah Goodman's Computation & Cognition lab, and founder of Ought Inc. Previously, he received his Ph.D. in Brain and Cognitive Sciences from MIT, where he was part of Prof. Josh Tenenbaum's Computational Cognitive Science group. He has worked on the design and implementation of probabilistic programming languages, on their application to cognitive modeling, and recently on dialog systems. He is broadly interested in leveraging machine learning to help people think.
Host: Marjan Ghazvininejad and Kevin Knight
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/
