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Conferences, Lectures, & Seminars
Events for February
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CS Colloquium: Vasilis Verroios (Stanford) - Combining Algorithms and Humans for Large-Scale Data Integration
Wed, Feb 01, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Vasilis Verroios , Stanford University
Talk Title: Combining Algorithms and Humans for Large-Scale Data Integration
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Modern enterprises collect data from their operations and the web, and strongly depend on the collected data to make important decisions. To analyze the collected data, enterprises need to first perform data integration, i.e., combine the data from the multiple sources to create a unified set.
Data integration involves some tasks that are still very hard for computer algorithms, like tasks involving images, video, natural language, or data semantics understanding. Since humans may be more accurate with such tasks, the approach of crowdsourcing has been proposed and applied by large companies and research organizations, over the last years. In crowdsourcing, humans are also involved, in order to enhance computer algorithms by completing small tasks, like classifying a forum comment as offensive or ironic. Crowdsourcing drastically improves the accuracy of the outcome compared to using only computer algorithms, however, it does not scale due to the large amount of time (and monetary compensation) required by humans. In this talk, I will discuss how to make crowdsourcing scalable for data integration.
Biography: Vasilis Verroios is a PhD candidate in the Computer Science Department, at Stanford University. His advisor is Hector Garcia-Molina. He received a B.S. and M.S. in Computer Science from the University of Athens, in 2006 and 2008, respectively. In the past, he has been a member of the "Management of Data, Information, & Knowledge Group" at the University of Athens, and he has worked for oDesk and Microsoft Research. His primary interests include data integration, data analytics, and data mining.
Host: Cyrus Shahabi
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Astani Civil and Environmental Engineering Seminar
Wed, Feb 01, 2017 @ 02:00 PM - 03:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Lawrence A. Bergman, Professor Emeritus, Department of Aerospace Engineering, University of Illinois at Urbana Champaign
Talk Title: Targeted Energy Transfer: Intentional Use of Strong Nonlinearity for Vibration and Shock Control
Abstract: For more than fifteen years, our research group has been developing and applying the concept of Targeted Energy Transfer (TET) as an effective strategy for passively managing energy flows in dynamical systems subject to broadband transient loading. The technology has been studied analytically, computationally, and experimentally in applications covering a range of scales from nano to macro. I will briefly explain the principles behind TET, followed by a discussion of several of these applications demonstrating the efficacy of the technology.
Biography: Professor Lawrence A. Bergman received the B.S. in Mechanical Engineering from the Stevens Institute of Technology, and the M.S. in Civil Engineering and Ph.D. in Applied Mechanics from Case Western Reserve University. Prior to graduate school, he was on the technical staff of TRW, Inc. and the Lord Corporation. His research has been primarily in the areas of structural dynamics and control, nonlinear dynamics, applied stochastic processes, system identification, and computational methods. He was editor-in-chief of the ASME Journal of Vibration and Acoustics from 2000 through 2004, and served on the Executive Committee of the Applied Mechanics Division of ASME from 2009 -“ 2014, the last year as Chair. Professor Bergman has been a faculty member at the University of Illinois at Urbana-Champaign since 1979, where he is a professor in the Department of Aerospace Engineering, an affiliate professor of the Departments of Civil and Environmental Engineering and of Mechanical Science and Engineering, and where he served as assistant dean of the College of Engineering during the 1996-97 academic year. He is a Fellow of the American Society of Mechanical Engineers and an Associate Fellow of the American Institute of Aeronautics and Astronautics.
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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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
Wed, Feb 01, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Georgios Fainekos, Associate Professor, Arizona State University (ASU)
Talk Title: Beyond Requirements Falsification: Semi-formal methods and tools for the analysis of Cyber-Physical Systems
Abstract: Correct-by-design synthesis methods for Cyber-Physical Systems (CPS) are still in their infancy for CPS with complex physical dynamics. For that reason, a combination of design theories for simpler systems and/or ad-hoc design approaches are utilized. Hence, numerous design and implementation errors are discovered while CPS are operational in the field. Such errors can have catastrophic effects to human life and to the economy. Over the last few years, requirements guided falsification methods have proven to be a practical approach to the verification problem of industrial size CPS. However, requirements falsification is just one component of the necessary tools for the development of safe and reliable CPS. In this talk, we provide an overview of our research in providing support for all the stages of the development for CPS, from formal requirements elicitation and mining to system conformance to on-line monitoring. Most of our methods have been implemented in a Matlab (TM) toolbox called S-TaLiRo (System's TemporAl LogIc Robustness). Finally, in this talk, we demonstrate that S-TaLiRo can provide answers to challenge problems from the automotive industry.
Biography: Georgios Fainekos is an Associate Professor at the School of Computing, Informatics and Decision Systems Engineering (SCIDSE) at Arizona State University (ASU). He is director of the Cyber-Physical Systems (CPS) Lab and he is currently affiliated with the NSF I/UCR Center for Embedded Systems (CES) at ASU. He received his Ph.D. in Computer and Information Science from the University of Pennsylvania in 2008 where he was affiliated with the GRASP laboratory. He holds a Diploma degree (B.Sc. & M.Sc.) in Mechanical Engineering from the National Technical University of Athens and an M.Sc. degree in Computer and Information Science from the University of Pennsylvania. Before joining ASU, he held a Postdoctoral Researcher position at NEC Laboratories America in the System Analysis & Verification Group. He is currently working on Cyber-Physical Systems (CPS) and robotics. In particular, his expertise is on formal methods, logic, artificial intelligence, optimization and control theory. His research has applications on automotive systems, medical devices, autonomous (ground and aerial) robots and human-robot interaction (HRI). In 2013, Dr. Fainekos received the NSF CAREER award. He was also recipient of the SCIDSE Best Researcher Junior Faculty award for 2013 and of the 2008 Frank Anger Memorial ACM SIGBED/SIGSOFT Student Award. Two of his conference papers have been nominated for student best paper awards.
Host: Paul Bogdan
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: Everyone Is Invited
Contact: Estela Lopez
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MHI CommNetS Seminar
Wed, Feb 01, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Nikolai Matni, Caltech
Talk Title: A system level approach to controller synthesis
Series: CommNetS
Abstract: Biological and advanced cyberphysical control systems often have limited, sparse, uncertain, and distributed communication and computing in addition to sensing and actuation. Fortunately, the corresponding plants and performance requirements are also sparse and structured, and this must be exploited to make constrained controller design feasible and tractable. We introduce a new "system level" (SL) approach involving three complementary SL elements. System Level Parameterizations (SLPs) generalize state space and Youla parameterizations of all stabilizing controllers and the responses they achieve, and combine with System Level Constraints (SLCs) to parameterize the largest known class of constrained stabilizing controllers that admit a convex characterization, generalizing quadratic invariance. SLPs also lead to a generalization of detectability and stabilizability, suggesting the existence of a rich separation structure, that when combined with SLCs, is naturally applicable to structurally constrained controllers and systems. We further provide a catalog of useful SLCs, most importantly including sparsity, delay, and locality constraints on both communication and computing internal to the controller, and external system performance. The resulting System Level Synthesis (SLS) problems that arise define the broadest known class of constrained optimal control problems that can be solved using convex programming. We end with an example that illustrates how this system level approach can systematically explore tradeoffs in controller performance, robustness, and synthesis/implementation complexity. This is joint work with Yuh-Shyang Wang and John C. Doyle at Caltech.
Biography: Nikolai is a postdoctoral scholar in Computing and Mathematical Sciences at the California Institute of Technology. He received the B.A.Sc. and M.A.Sc. in Electrical Engineering from the University of British Columbia, and the Ph.D. in Control and Dynamical Systems from the California Institute of Technology in June 2016. His research interests broadly encompass the use of layering, dynamics, control and optimization in the design and analysis of complex cyber-physical systems; current application areas include software defined networking and sensorimotor control.
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: Finale Doshi-Velez (Harvard) - Characterizing and Conquering Non-Identifiability in Non-negative Matrix Factorization
Thu, Feb 02, 2017 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Finale Doshi-Velez, Harvard
Talk Title: Characterizing and Conquering Non-Identifiability in Non-negative Matrix Factorization
Series: Yahoo! Labs Machine Learning Seminar Series
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium. Part of Yahoo! Labs Machine Learning Seminar Series.
Nonnegative matrix factorization (NMF) is a popular dimension reduction technique that produces interpretable decomposition of the data into parts. However, this decomposition is often not identifiable, even beyond simple cases of permutation and scaling. Non-identifiability is an important concern in practical data exploration settings, in which the basis of the NMF factorization may be interpreted as having some kind of meaning: it may be important to know that other non-negative characterizations of the data were also possible. While other studies have provide criteria under which NMF is unique, in this talk I'll discuss when and how an NMF might *not* be unique. Then I'll discuss some novel algorithms for characterizing the posterior in Bayesian NMF.
Biography: Finale Doshi-Velez is an Assistant Professor in Computer Science at Harvard University. Prior to that, she was a NSF CiTraCS postdoctoral fellow at Harvard Medical School and a Marshall Scholar at the University of Cambridge. She completed her PhD at MIT. Her interests lie in the intersection of healthcare and machine learning.
Host: Yan Liu
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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AI Seminar
Fri, Feb 03, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Elias Bareinboim, Assistant Professor, Purdue University
Talk Title: The Data-Fusion Problem: Causal Inference and Reinforcement Learning
Abstract: Machine Learning is usually dichotomized into two categories, passive and active which, by and large, are studied separately. Reality is more demanding. Passive and active modes of operation are but two extremes of a rich spectrum of data collection modes that generate the bulk of the data available in practical, large scale situations. In typical medical explorations, for example, data from multiple observations and experiments are collected, coming from distinct experimental setups, different sampling conditions, and heterogeneous populations. Similarly, in a more basic setting, a baby learns from its environment by both passively observing others and interacting with its environment by actively performing interventions. In this task, I will review the theory of structural causality and use it to explain the relationship between causal inference and reinforcement learning . Further, I will formulate and discuss a collection of inference tasks that lie in the intersection of RL and causal inference, including personalized decision making.
Biography: Elias Bareinboim is an assistant professor in the Department of Computer Science at Purdue University. His research focuses on causal and counterfactual inference and their applications to data driven fields. Bareinboim received a Ph.D. in Computer Science from UCLA advised by Judea Pearl. His doctoral thesis was the first to propose a general solution to the problem of data fusion and to provide practical methods for combining datasets generated under different experimental conditions. Bareinboims recognitions include IEEE AIs 10 to Watch, the Dan David Prize Scholarship, the Yahoo! Key Scientific Challenges Award, and the 2014 AAAI Outstanding Paper Award.
Host: Mayank Kejriwal
Audiences: Everyone Is Invited
Contact: Kary Lau
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USC Physics Seminar, Eli Kapon, Friday, February 3, 2017 in SSL 150 @ 2:00pm
Fri, Feb 03, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Eli Kapon, Laboratory of Physics of Nanostructures, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Talk Title: Quantum Photonics with Ordered Quantum Dot and Quantum Wire Systems
Abstract: Quantum wire (QWR) and quantum dot (QD) systems offer means for tailoring the electronic structure of semiconductors thanks to multi-dimensional quantum confinement. By placing them in confined photonic structures (waveguides, cavities) it is possible to tailor light-matter interaction via the introduced modifications in the density of states of excitons and photons. We review the technology of ordered QWR and QD structures grown by metallolrganic vapor phase epitaxy on patterned substrates and their integration with photonic components. Tailoring exciton wavefunctions, controlling their recombination dynamics, and observing cavity quantum electrodynamic effects in the integrated structures are described. Applications in quantum information technology and ultralow threshold lasers are discussed.
Biography: Eli Kapon received his Ph.D. in physics from Tel Aviv University, Israel in 1982. He then spent two years at the California Institute of Technology, Pasadena, as a Chaim Weizmann Research Fellow, and then nine years at Bellcore, New Jersey, as member of technical staff and District Manager. Since 1993 he has been Professor of Physics of Nanostructures at the Swiss Federal Institute of Technology in Lausanne (EPFL), where he heads the Laboratory of Physics of Nanostructures. In 1999-2000 he was a Sackler Scholar at the Mortimer and Raymond Sackler Institute of Advanced Studies in Tel Aviv University, Israel. During that period he helped establishing the Tel Aviv University Center for Nanoscience and Nanotechnology and served as its first Director from 2000 to 2002. In 2001 he founded the start up BeamExpress, serving as its Chief Scientist. His research interests include quantum- and nano-photonics, low-dimensional semiconductors, and vertical cavity semiconductor lasers. Prof. Kapon is Fellow of the Optical Society of America, the Institute of Electrical and Electronics Engineers, and the American Physical Society of America, a recipient of a 2007 Humboldt Research Award, and a Photonics Society Distinguished Lecturer for 2105-2017.
Host: Physics Seminar, Quantum Information - Condensed Matter - Biophysics
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Feb 03, 2017 @ 02:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Vivienne Sze, Professor at MIT
Talk Title: Energy-Efficient Hardware for Embedded Vision and Deep Convolutional Neural Network
Host: Prof. Dina Reda El-Damak
More Information: MHI Seminar Series IS - Vivienne Sze.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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BME Special SeminarFri, Feb 03, 2017 @ 02:30 PM - 04:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Rich Roberts, PhD, Department Chair, USC Viterbi Mork Department of Materials Science & Chemical Engineering
Talk Title: TBA
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 Recurrent Neural Networks for Narrative Prediction
Fri, Feb 03, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Melissa Roemmele, USC ICT
Talk Title: Recurrent Neural Networks for Narrative Prediction
Series: Natural Language Seminar
Abstract: Narrative prediction involves predicting what happens next in a story. This task has a long history in AI research but is now getting more recognition in the NLP community. In this talk I will describe three different evaluation schemes for narrative prediction, one of which the Story Cloze Test is the shared task for this years LSDSem workshop at EACL. I will present my ongoing efforts to develop Recurrent Neural Network based models that succeed on these evaluation frameworks, and discuss the particular challenges posed by each of them.
Biography: I am a PhD candidate at the USC Institute for Creative Technologies advised by Andrew Gordon in the Narrative Group. My thesis research explores machine learning approaches to automatically generating text based stories. I am interested in using this research to stimulate creativity in writing. More broadly, I am excited by any opportunity to use automated analysis of text data to give people new insights and ideas.
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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CS Colloquium: Leilani Battile (CSAIL MIT) - Behavior-Driven Optimizations for Big Data Exploration
Mon, Feb 06, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Leilani Battile , CSAIL MIT
Talk Title: Behavior-Driven Optimizations for Big Data Exploration
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
The physical and biological sciences are becoming more data driven, often due overwhelming quantities of data collected from satellites, telescopes, sequencers, and other sensors. One of the key issues for scientists who work with large datasets is efficient visualization of their data to extract patterns, observe anomalies, and debug their workflows. Though a variety of visualization tools exist to help people make sense of their data, these tools often rely on database management systems (or DBMSs) for data processing and storage; and unfortunately, DBMSs fail to process the data fast enough to support a fluid, interactive visualization experience.
My work blends optimization techniques from databases and methodology from HCI and visualzation in order to support interactive and iterative exploration of large datasets. In this talk, I will discuss Sculpin, a visual exploration system that learns user exploration patterns automatically, and exploits these patterns to pre-fetch data ahead of users as they explore. I will show that Sculpin's pre-fetching techniques provide significant performance benefits compared to existing systems. I will then discuss our ongoing work with Sculpin, which aims to avoid wasting computational resources, while still providing a fluid, interactive exploration experience for users. To do this, we combine data-prefetching with incremental data processing and visualization-focused caching optimizations, and incorporate these techniques in Sculpin to further boost performance.
Biography: Leilani Battile is a Computer Science Ph.D. candidate in the CSAIL Database Group at MIT, advised by Prof. Michael Stonebraker. Her research interests lie at the intersection of data management, user interface design, and visual analytics, with the aim of building intuitive and scalable database exploration tools. She was a National Science Foundation Graduate Fellow from 2011 to 2013. She obtained a M.S. from MIT in 2013, and a B.S. in Computer Engineering from the University of Washington in 2011.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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TBA
Mon, Feb 06, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: J. Jack Whalen, PhD, Assistant Professor of Research Ophthalmology, USC Roski Eye Institute, Keck School of Medicine
Talk Title: Novel Biomaterials Strategies to Treat Ocular Trauma
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, Feb 06, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Karl Henrik Johansson, Professor, KTH Royal Institute of Technology.
Talk Title: Collaborative Road Freight Transport
Abstract: Freight transportation is of outmost importance for our society. Road transporting accounts for about 26% of all energy consumption and 18% of greenhouse gas emissions in the European Union. Goods transport in the EU amounts to 3.5 trillion tonne-km per year with 3 million people employed in this sector, whereas people transport amounts to 6.5 trillion passenger-km with 2 million employees. Despite the influence the transportation system has on our energy consumption and the environment, road goods transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this talk, we will discuss how modern information and communication technology supports a cyber-physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save more than 10% of their fuel consumption. Control and estimation challenges and solutions on various level of this transportation system will be presented. It will be argued that a system architecture utilizing vehicle-to-vehicle and vehicle-to-infrastructure communication enable optimal and safe control of individual trucks as well as optimised vehicle fleet collaborations and new markets. Extensive experiments done on European highways will illustrate system performance and safety requirements. The presentation will be based on joint work over the last ten years with collaborators at KTH and at the truck manufacturer Scania.
Biography: Karl H. Johansson is Director of the Stockholm Strategic Research Area ICT The Next Generation and Professor at the School of Electrical Engineering, KTH Royal Institute of Technology. He received MSc and PhD degrees in Electrical Engineering from Lund University. He has held visiting positions at UC Berkeley, Caltech, NTU, HKUST Institute of Advanced Studies, and NTNU. His research interests are in networked control systems, cyber-physical systems, and applications in transportation, energy, and automation. He is a member of the IEEE Control Systems Society Board of Governors and the European Control Association Council. He has received several best paper awards and other distinctions, including a ten-year Wallenberg Scholar Grant, a Senior Researcher Position with the Swedish Research Council, and Future Research Leader Award from the Swedish Foundation for Strategic Research. He is Fellow of the IEEE and IEEE Distinguished Lecturer.
Host: Bhaskar Krishnamachari
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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USC Stem Cell Seminar: Laura Niklason, Yale University
Tue, Feb 07, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Laura Niklason, Yale University
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: Heather Culbertson (Stanford University) - Realistic and Intuitive Haptic Feedback for Communication in Virtual and Real-World Environments
Tue, Feb 07, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Heather Culbertson, Stanford University
Talk Title: Realistic and Intuitive Haptic Feedback for Communication in Virtual and Real-World Environments
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
The haptic (touch) sensations felt when interacting with the physical world create a rich and varied impression of objects and their environment. Humans are capable of gathering a significant amount of information through touch with their environment, allowing them to assess object properties and qualities, dexterously handle objects, and communicate social cues and emotions. Humans are spending significantly more time in the digital world, however, and are increasingly interacting with people and objects through a digital medium. Unfortunately, digital interactions remain unsatisfying and limited, representing the human as having only two sensory inputs: visual and auditory.
This talk will focus on the investigation of haptic devices and rendering algorithms to provide humans with touch information when communicating through a computer. I will present a background on the sense of touch, and illustrate how we can leverage this knowledge in order to design haptic devices and rendering systems that allow the human to communicate through the digital world in a natural and intuitive way. I will highlight contributions I have made in furthering haptic realism in virtual reality through the creation of highly realistic virtual objects. These objects are created by modeling high-frequency acceleration, force, and speed data recorded during physical interactions and displaying the appropriate haptic signals during rendering. I will then describe advances I have made in novel wearable haptic devices for communicating information to a human using intuitive and natural cues.
Biography: Heather Culbertson is a Postdoctoral Research Fellow in the Department of Mechanical Engineering at Stanford University where she works in the Collaborative Haptics and Robotics in Medicine (CHARM) Lab. She received her PhD in the Department of Mechanical Engineering and Applied Mechanics (MEAM) at the University of Pennsylvania in 2015 working in the Haptics Group, part of the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory. She completed a Masters in MEAM at the University of Pennsylvania in May of 2013, and earned a BS degree in mechanical engineering at the University of Nevada, Reno in 2010.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute Seminar, ISE 651
Tue, Feb 07, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Dusan M. Stipanovic, Associate Professor, University of Illinois at Urbana-Champaign
Talk Title: Control of Dynamic Systems with Multiple Objectives
Abstract: The challenges of controlling multiple dynamic systems with multiple objectives include problems in multi-player dynamic games, multi-objective optimization, and decentralized control and estimation. The additional complexities are caused by the existence of non linearities, time delays and perturbations in dynamic models, as well as various state, input and communication constraints. In this talk, a number of results related to multi-objective control of multiple dynamic systems will be presented. To illustrate these results some particular examples of controlling multiple dynamical systems in pursuit of accomplishing multiple objectives such as guaranteed capture or evasion, collision avoidance, tracking, and coverage control, will be presented.
Biography: Dr. Dusan Stipanovic received his B.S. degree in electrical engineering from the University of Belgrade, Belgrade, Serbia, in 1994, and the M.S.E.E. and Ph.D. degrees (under supervision of Professor Dragoslav Siljak) in electrical engineering from Santa Clara University, Santa Clara, California, in 1996 and 2000, respectively. Dr. Stipanovic had been an Adjunct Lecturer and Research Associate with the Department of Electrical Engineering at Santa Clara University (1998-2001), and a Research Associate in Professor Claire Tomlin's Hybrid Systems Laboratory of the Department of Aeronautics and Astronautics at Stanford University (2001-2004). In 2004 he joined the University of Illinois at Urbana-Champaign where he is now Associate Professor in the Department of Industrial and Enterprise Systems Engineering and Coordinated Science Laboratory. He is a visiting Professor in the School of Electrical Engineering, University of Belgrade, Serbia, and in the Robotics and Telematics Department at the University of Wuerzburg, Germany, and also held a visiting faculty position in the EECS Department at the University of California at Berkeley. His research interests include decentralized control and estimation, stability theory, optimal control, and dynamic games with applications in control of autonomous vehicles, circuits, and medical robotics. Dr. Stipanovic served as an Associate Editor on the Editorial Boards of the IEEE Transactions on Circuits and Systems I and II. Currently he is an Associate Editor for Journal of Optimization Theory and Applications.
Host: Professor Ali Abbas
More Information: February 7, 2017_Stipanovic.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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The Business of Oil and Gas
Wed, Feb 08, 2017 @ 05:00 PM - 06:30 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Mr. Jim Crompton, Reflections Data Consulting
Talk Title: Integrated Operations Centers: A New Paradigm for working in the Digital Oilfield
Series: USC Energy Institute Seminar Series
Host: USC Energy Institute
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Juli Legat
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CS Colloquium: Dorsa Sadigh (UC Berkeley) -Towards a Theory of Safe and Interactive Autonomy
Thu, Feb 09, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dorsa Sadigh, UC Berkeley
Talk Title: Towards a Theory of Safe and Interactive Autonomy
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Today's society is rapidly advancing towards cyber-physical systems (CPS) that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. The safety-critical nature of these systems requires us to provide provably correct guarantees about their performance in interaction with humans. The goal of my research is to enable such human-cyber-physical systems (h-CPS) to be safe and interactive. I aim to develop a formalism for design of algorithms and mathematical models that facilitate correct-by-construction control for safe and interactive autonomy.
In this talk, I will first discuss interactive autonomy, where we use algorithmic human-robot interaction to be mindful of the effects of autonomous systems on humans, and further leverage these effects for better safety, efficiency, coordination, and estimation. I will then talk about safe autonomy, where we provide correctness guarantees, while taking into account the uncertainty arising from the environment. Further, I will discuss a diagnosis and repair algorithm for systematic transfer of control to the human in unrealizable settings. While the algorithms and techniques introduced can be applied to many h-CPS applications, in this talk, I will focus on the implications of my work for semi-autonomous driving.
Biography: Dorsa Sadigh is a Ph.D. candidate in the Electrical Engineering and Computer Sciences department at UC Berkeley. Her research interests lie in the intersection of control theory, formal methods, and human-robot interactions. Specifically, she works on developing a unified framework for safe and interactive autonomy. Dorsa received her B.S. from Berkeley EECS in 2012. She was awarded the NDSEG and NSF graduate research fellowships in 2013. She was the recipient of the 2016 Leon O. Chua department award and the 2011 Arthur M. Hopkin department award for achievement in the field of nonlinear science, and she received the Google Anita Borg Scholarship in 2016.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Neuromorphic Systems to Reverse Engineer Reflex Function
Thu, Feb 09, 2017 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Professor Francisco Valero-Cuevas, USC
Talk Title: Neuromorphic Systems to Reverse Engineer Reflex Function
Abstract: The objective of this work is to build a neuromorphic robotic system that can interact with the physical world by implementing neuromechanical principles. It is a faithful implementation of the spinal circuitry responsible for the afferentation of muscles and is capable of producing both normal and pathological functions.
We used state-of-the-art models of muscle spindle mechanoreceptors with fusimotor drive, monosynaptic circuitry of the stretch reflex, and alpha motoneuron recruitment and rate coding. This multi-scale, hybrid system driven by populations of 1024 spiking neurons, emulated the physiological characteristics of the afferented mammalian muscles. We implemented these models on field-programmable gate arrays (FPGAs) which are capable of running these complex computations in real-time. The FPGAs control the forces of two muscles acting on a joint via long tendons. We performed ramp-and-hold perturbations and systematically explored a range of muscle spindle gains (fusimotor drive) to characterize the stretch reflex response in different phases of the perturbation. Finally, we explored the fidelity of four models for isometric muscle force production by testing their responses to rate-coding using spike trains and produced force ramps.
This autonomous integrated system was self-stable and the closed-loop behavior of populations of muscle spindles, alpha and gamma motoneurones, and muscle fibers emulated muscle tone and function. Sweeping the range of muscle spindle gains provided us with a subset of values that produced tenable physiological and pathological responses. Moreover, isometric force generation revealed that the dynamic response in the tendons is very sensitive to tendon elasticity, especially at high firing rates.
This hybrid, neuromorphic, neuromechanical system is a precursor to neuromorphic robotic systems. It provides a platform to study healthy function and the potential spinal and/or supraspinal sources of pathologic behavior.
Biography: I attended Swarthmore College from 1984-88 where I obtained a BS degree in Engineering. After spending a year in the Indian subcontinent as a Thomas J Watson Fellow, I joined Queen's University in Ontario and worked with Dr. Carolyn Small. The research for my Masters Degree in Mechanical Engineering at Queen's focused on developing non-invasive methods to estimate the kinematic integrity of the wrist joint.
In 1991, I joined the doctoral program in the Design Division of the Mechanical Engineering Department at Stanford University. I worked with Dr. Felix Zajac developing a realistic biomechanical model of the human digits. This research, done at the Rehabilitation R & D Center in Palo Alto, focused on predicting optimal coordination patterns of finger musculature during static force production.
After completing my doctoral degree in 1997, I joined the core faculty of the Biomechanical Engineering Division at Stanford University as a Research Associate and Lecturer. In 1999, I joined the faculty of the Sibley School of Mechanical and Aerospace Engineering at Cornell University as Assistant Professor, and was tenured in 2005. In 2007, I joined the faculty at the Department of Biomedical Engineering, and the Division of Biokinesiology & Physical Therapy at the University of Southern California as Associate Professor; where I was promoted to Full Professor in 2011. In 2013 I was elected Senior Member of the IEEE, and in 2014 to the College of Fellows of the American Institute for Medical and Biological Engineers.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Lyman L. Handy Colloquia
Thu, Feb 09, 2017 @ 12:45 PM - 01:50 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dr. Rampi Ramprasad , University of Connecticut
Talk Title: Rational Computation-Guided Design of Polymer Dielectrics
Series: Lyman Handy Colloquia
Host: Professor Rajiv Kalia
Location: James H. Zumberge Hall Of Science (ZHS) - 159
Audiences: Everyone Is Invited
Contact: Martin Olekszyk
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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
Thu, Feb 09, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Justinian Rosca , Siemens Corporate Technology, Princeton, NJ
Talk Title: Synchronizing the Real and Digital Worlds: Lessons from Autonomous Cars
Abstract: Computational estimation problems for real-world applications are rife with myriad sources of uncertainty from noise, sensor inaccuracies, incompleteness of the data, unmeasured effects, calibration errors, to physical principles not modeled in computation. We are interested in inference and reasoning frameworks with capabilities for characterizing and handling uncertainty throughout the computational process in all phases of the unified digital twin of a cyber physical system.
In this talk I present examples from my research on uncertainty handling for two problems. Each deals with a different phase for building the digital twin of an automated system, such as an autonomously driven connected car. Automated vehicle technology senses the driving environment and operates a vehicle with limited or even without human input. Digital twins offer the potential to unify models across the lifecycle phases of a complex cyber physical system, from design (CAD models), engineering (CAE models), production (CAM and simulation models), to operation and maintenance (PHM and reliability models).
The first use case is from the engineering phase of an autonomous vehicle that drives safely through intersections. Simulation is a powerful cost-effective method for developing, testing, and evaluating various components of new technologies, where a limited initial market penetration and unknown human behavioral responses are the status-quo. Realistic modeling of how connected vehicles "talk" to each other while moving in traffic is essential for large scale simulations of time-critical applications. However, there is no widely agreed upon physical model for Dedicated Short Range Communications (DSRC) over the 75 MHz of spectrum using the IEEE 802.11p standard. How do we sum up and exploit real world measurements of interference, fading, antennas, weather, environment type, vehicle movement and traffic density, which are difficult to characterize and rich in uncertainty at all levels? Brought into simulation, these will affect the very algorithms that control the vehicle and acquire new data. Therefore, we bring data from the real world into the digital twin to affect the design and engineering phases and vet the application on a large scale. At the other end of the digital twin, the second use case is about edge intelligence in a vehicle perpetually connected to its physical world through hundreds of sensors and communication links, which offer fast analogue and digital data to be exploited in understanding the patterns of operation for machine health management and ultimately, for control. Again we face the challenge of processing a river of data and reasoning with uncertainty pro-actively about the past and the future, to explain system dynamics, gain immediate insights for control, and connect to the prior lifecycle phases of design and engineering.
Biography: Justinian Rosca is Senior Key Expert of Siemens Corp., Corporate Technology in Princeton NJ, where he has been managing research and innovation since 1999. He received his Ph.D. and M.S. degrees in Computer Science from the University of Rochester, NY. He also holds the M.S. degree in Computers and Control Engineering from Polytechnic University Bucharest. He was Affiliate Professor at the University of Washington, 2008-2011, and obtained a certificate in executive management for innovation, from the University of Pennsylvania, Wharton School of Business.
Dr. Rosca's primary research interests span sensing and communication, statistical signal processing, machine learning, probabilistic inference, and artificial intelligence, with an emphasis on embedded intelligence in autonomous systems. Dr. Rosca holds close to 50 patents, 100 publications in the areas of signal processing, machine learning, and cyber-physical systems, and co-authored two books in mathematics and signal processing. Several of his innovations are at the foundation of Siemens' multi-channel digital hearing aids technology, and affect the quality of hearing for millions of people worldwide. His scientific contributions were transferred into a variety of products and systems such as microphone array technologies for hearing aids and mobile phones, adaptive multimedia wireless network management, traffic services for connected vehicles, and edge analytics in industry, and earned him multiple Siemens business unit awards. He served as program chair of the 6th Independent Component Analysis and Blind Signal Separation International Conference, chair of the Neural Information and Processing Systems workshop on Sparse Representations in Signal Processing, and recently as chair of the Data Challenge 2015 and 2016 competitions of the Prognostics and Health Management Society.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
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PhD Defense: Analysis and Modeling of Multi-Level Dynamics of Multimodal Behavior in Affective Human Interactions
Thu, Feb 09, 2017 @ 02:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Zhaojun Yang, University of Southern California, PhD Candidate
Talk Title: Analysis and Modeling of Multi-Level Dynamics of Multimodal Behavior in Affective Human Interactions
Abstract: Human communication is a dynamical and interactive process that is established on a common ground of conveying emotions, achieving the interaction goals and sharing mutual interests of the interaction participants. Such an interactive process naturally induces a multi-level dynamical flow along various verbal and nonverbal behavior dimensions of spoken words, speech prosody, body gestures, and facial expressions. As one of the major components that shape the structure of social interactions, emotions greatly affect the multi-level dynamics of multimodal behavior throughout the course of an interaction. This thesis, from three perspectives, explores computational methodologies to understand, analyze and model human behaviors dynamics that relate to and arise from affective processes underlying human interactions: 1) modeling the dynamics of body gesture expression of emotions; 2) studying how multimodal behavior channels, speech and body particularly, of an individual dynamically interact with one another towards emotion expression; and 3) exploring interpersonal coordination of multimodal behavior induced in human interactions.
Defense committee: Prof. Shrikanth Narayanan (Chair), Prof. C.-C. Jay Kuo, Prof. Gayla Margolin (Outside member)
Biography: Zhaojun Yang is a PhD candidate in Electrical Engineering at the University of Southern California (USC). She received her B.E. Degree from University of Science and Technology of China (USTC) 2009 and M.Phil. Degree from Chinese University of Hong Kong (CUHK) 2011. She was awarded with the USC Annenberg Fellowship (2011-2015). Her work (with S. S. Narayanan) has won the Best Student Paper Award at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2016. Her research interests include Affective Computing, Machine Learning, and Human-centered multimodal signal processing.
Host: Shrikanth Narayanan
Location: Ronald Tutor Hall of Engineering (RTH) - 320
Audiences: Everyone Is Invited
Contact: Tanya Acevedo-Lam/EE-Systems
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Seminars in Biomedical Engineering
Fri, Feb 10, 2017 @ 02:30 PM - 04:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Sook-Lei Liew, Assistant Professor, Occupational Therapy, Herman Ostrow School of Dentistry of USC
Talk Title: Large scale neuroimaging and neuromodulation to promote motor recovery after stroke
Series: Seminars in BME (Lab Rotations)
Abstract: Stroke is a leading cause of adult long term disability, and up to 2/3 of stroke survivors do not fully recover, despite intensive therapy. Identifying and personalizing rehabilitation treatments based on each patient's neurological and behavioral profile could greatly enhance the post-stroke outcomes. In this talk, I will discuss a two-pronged approach to address this problem. First, we are characterizing how specific neuroanatomical changes relate to motor recovery on a large scale. In partnership with ENIGMA Center for Worldwide Medicine, Imaging, and Genomics, we have developed an ENIGMA working group on stroke recovery to harmonize stroke neuroimaging efforts around the world, with an initial goal of n>3000 MRIs. Our preliminary data shows promising results, with specific post-stroke neuroanatomical motor regions relating to motor impairment and recovery, and results becoming more robust as data across sites is combined. Second, we are developing and evaluating neuromodulatory approaches to affect brain activity in key regions after stroke, using noninvasive brain stimulation and brain computer interfaces to enhance therapeutic outcomes. Preliminary work using transcranial direct current stimulation, real-time fMRI connectivity neurofeedback and a portable EEG-based virtual reality neurofeedback system will be discussed, along with future implications of this work for translational research.
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-THE LIMITS OF UNSUPERVISED SYNTAX AND THE IMPORTANCE OF GROUNDING IN LANGUAGE ACQUISITION
Fri, Feb 10, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Yonatan Bisk, USC/ISI
Talk Title: THE LIMITS OF UNSUPERVISED SYNTAX AND THE IMPORTANCE OF GROUNDING IN LANGUAGE ACQUISITION
Series: Natural Language Seminar
Abstract: The future of self driving cars, personal robots, smart homes, and intelligent assistants hinges on our ability to communicate with computers. The failures and miscommunications of Siri style systems are untenable and become more problematic as machines become more pervasive and are given more control over our lives. Despite the creation of massive proprietary datasets to train dialogue systems, these systems still fail at the most basic tasks. Further, their reliance on big data is problematic. First, successes in English cannot be replicated in most of the six thousand plus languages of the world. Second, while big data has been a boon for supervised training methods, many of the most interesting tasks will never have enough labeled data to actually achieve our goals. It is, therefore, important that we build systems which can learn from naturally occurring data and grounded, situated interactions.
In this talk I will discuss work from my thesis on the unsupervised acquisition of syntax which harnesses unlabeled text in over a dozen languages. This exploration leads us to novel insights into the limits of semantics free language learning. Having isolated these stumbling blocks I will then present my recent work on language grounding where we attempt to learn the meaning of several linguistic constructions via interaction with the world.
Biography: Yonatan Bisk has research that focuses on Natural Language Processing from naturally occurring data unsupervised and weakly supervised data. He is a postdoc researcher with Daniel Marcu at USCs Information Sciences Institute. Previously, he received his PhD from the University of Illinois at Urbana Champaign under Julia Hockenmaier and his BS from the University of Texas at Austin.
Host: Marjan Ghazvininejad and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 6th Flr -CR#689 (ISI/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, Feb 10, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Aycut Ayca and Arsalan Heydarian, Ph.D. Students -Astani Civil Engineering Department
Talk Title: TBA
Abstract: TBA
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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CS Colloquium: Anirudh Sivaraman (CSAIL MIT) - Making the fastest routers programmable
Mon, Feb 13, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Anirudh Sivaraman, CSAIL MIT
Talk Title: Making the fastest routers programmable
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Historically, the evolution of network routers was driven primarily by performance. Recently, owing to the need for better control over network operations and the constant demand for new features, programmability of routers has become as important as performance.
However, today's fastest routers, which run at line rate, use fixed-function hardware, which cannot be modified after deployment. I will describe two router primitives we have developed to build programmable routers at line rate. The first is a programmable pocket scheduler. The second is a way to execute stateful packet-processing algorithms to manage network resources. Together, these primitives allow us to program several packet-processing functions at line rate, such as in-network congestion control, active queue management, data-plane load balancing, network measurement, and packet scheduling.
This talk is based on joint work with collaborators at MIT, Barefoot Networks, Cisco Systems, Microsoft Research, Stanford University, and the University of Washington.
Biography: Anirudh Sivaraman is a Ph.D. student at MIT, advised by Hari Balakrishnan and Mohammad Alizadeh. His recent research work has focused on hardware and software for programmable high-speed routers. He has also been actively involved in the design and evolution of the P4 language for programmable network devices. His past research includes work on congestion control, network emulation, improving Web performance, and network measurement. He received the MIT EECS department's Frederick C. Hennie III Teaching Award in 2012 and shared the Internet Research Task Force's Applied Networking Research Prize in 2014.
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, Feb 13, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: John Lasch, Director, USC AMI
Talk Title: Technology Development
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, Feb 13, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Michael Shlesinger, Office of Naval Research
Talk Title: Pitfalls and Paradoxes in the History of Probability Theory
Abstract: This lecture traces the history of probability theory from the throwing of bones, sticks, and dice to modern times. Early 18th century books, Jacob Bernouill's "The Art of Conjecturing" and Abraham DeMoivre's "The Doctrine of Chances" were rich with new mathematics, insight and gambling odds. Progress was often made by confronting paradoxes. The first of these confused probabilities with expectations and was explained in the Pascal-Fermat letters of 1654. The St. Petersburg Paradox involved a distribution with an infinite first moment, and Levy discovered a whole class of probabilities with infinite moments that have found a surprising utility in physics connected to fractals. Through conditional probabilities, Bayes introduced what later has become hypothesis testing. Arriving at two different answers, the Bertrand paradox involved measure theory for continuous probabilities, Poisson discovered that adding random variables need not always produce the Gaussian, and Daniel Bernoulli and D'Alembert argued over the probabilities for the safety of smallpox vaccinations. Using these and other anecdotes, this lecture discusses vignettes that have brought us to today's widespread use of probability and statistics.
Biography: Dr. Michael Shlesinger manages the nonlinear physics program at the Office of Naval Research. He has published over 200 scientific papers on topics in stochastic processes, glassy materials, proteins, neurons, and nonlinear dynamics. He is a Fellow of the American Physical Society and was a Divisional Associate Editor of the Physical Review Letters. In 2006 he received ONR's Saalfeld Award for Outstanding Lifetime Achievement in Science, and earlier the federal government's Presidential Rank Award for Meritorious Senior Professionals, and the Navy Superior Civilian Service Award. He held the Kinnear Chair in Physics at the USNA, was the Michelson Lecturer at the USNA, the Regents' Lecturer at UCSD and received the U. Maryland's Distinguished Postdoc Alum award. His Ph. D., in Physics, is from the U. of Rochester in 1975, and his 1970 B.S. in Mathematics and Physics is from SUNY Stony Brook.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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USC Stem Cell Seminar: Christine Brown, City of Hope
Tue, Feb 14, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Christine Brown, City of Hope
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: Aurojit Panda (UC Berkeley) - A New Approach to Network Functions
Tue, Feb 14, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Aurojit Panda, UC Berkeley
Talk Title: A New Approach to Network Functions
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Modern networks do far more than just deliver packets, and provide network functions -- including firewalls, caches, and WAN optimizers -” that are crucial for scaling networks, ensuring security and enabling new applications. Network functions were traditionally implemented using dedicated hardware middleboxes, but in recent years they are increasingly being deployed as VMs on commodity servers. While many herald this move towards network function virtualization (NFV) as a great step forward, I argue that accepted virtualization techniques are ill-suited to network functions. In this talk I describe NetBricks -” a new approach to building and running virtualized network functions that speeds development and increases performance. I end the talk by discussing the implications of being able to easily create and insert new network functions.
Biography: Aurojit Panda is a PhD candidate in Computer Science at the University of California Berkeley, where he is advised by Scott Shenker . His work spans programming languages, networking and systems, and his recent work has investigated network verification, consensus algorithms in software defined networks and frameworks for building network functions.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute Seminar, ISE 651
Tue, Feb 14, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Oguzhan Alagoz, Associate Professor, University of Wisconsin-Madison
Talk Title: A Mathematical Modeling Framework to Personalize Mammography Screening Decisions
Abstract: Breast cancer is the most common non-skin cancer and the second leading cause of cancer-death in US women. Although mammography is the most effective modality for breast cancer diagnosis, it has several potential risks, including high false positive rates, which are not very rare. Therefore, the balance of benefits and risks, which depend on personal characteristics, is critical in designing a mammography screening schedule. In contrast to prior research and existing guidelines which consider population-based screening recommendations, we propose a personalized mammography screening policy based on the prior screening history and personal risk characteristics of women.
We formulate a finite-horizon partially observable Markov decision process (POMDP) model for this problem. Our POMDP model incorporates two methods of detection (self or screen), age-specific unobservable disease progression, and age-specific mammography test characteristics. We use a validated micro-simulation model based on real data in estimating the parameters and solve this POMDP model optimally for individual patients. Our results show that our proposed personalized screening schedules outperform the existing guidelines with respect to the total expected quality-adjusted life years, while significantly decreasing the number of mammograms. We further find that the mammography screening threshold risk increases with age. We derive several structural properties of the model, including the sufficiency conditions that ensure the existence of a control-limit policy.
Biography: Dr. Oguzhan Alagoz is currently an Associate Professor of Industrial and Systems Engineering at the University of Wisconsin-Madison. He received his BS from Bilkent University in 1997, MS from Middle East Technical University in 2000, and PhD in industrial engineering from the University of Pittsburgh in 2004. He worked as a visiting assistant professor of Operations at the Weatherhead School of Management of Case Western Reserve University between 2004 and 2005. His research interests include stochastic optimization, medical decision making, completely and partially observable Markov decision processes, simulation, risk-prediction modeling, health technology assessment, and scheduling. He is on the editorial boards of Operations Research, IIE Transactions, and IIE Transactions on Healthcare Engineering and previously served on the board of Medical Decision Making. He has received various awards including a CAREER award from National Science Foundation (NSF), outstanding young industrial engineer in education award from IIE, Dantzig Dissertation Honorable Mention Award from INFORMS, 2nd place award from INFORMS Junior Faculty Interest Group best paper competition, best paper award from INFORMS Service Science Section, and best poster award from UW Carbone Comprehensive Cancer Center. He has been the principal investigator and co-investigator on grants more than $3.5 million funded by NSF and NIH.
Host: Professor Phebe Vayanou
More Information: February 14, 2017_Alagoz.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium: Theodoros Rekatsinas (Stanford University) - Data Integration with Unreliable Sources
Wed, Feb 15, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Theodoros Rekatsinas, Stanford University
Talk Title: Data Integration with Unreliable Sources
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Data integration is an essential element of data-intensive science and modern analytics. Users often need to combine data from different sources to gain new scientific knowledge, obtain accurate insights, and create new services. However, today's upsurge in the number and heterogeneity-”in terms of format and reliability-”of data sources limits the ability of users to reason about the value of data. This raises the fundamental questions: what makes a data source useful to end users, how can we integrate unreliable data, and which sources we need to combine to maximize the user's utility?
In this talk, I discuss how to assess and leverage the quality and reliability of data to make data integration more efficient. Specifically, I demonstrate how statistical learning is the key to managing large volumes of heterogeneous sources effectively. Building upon this observation, I introduce new solutions to classical data integration problems, such as data conflict resolution and data cleaning, and show that these solutions outperform their traditional counterparts by large margins. I finish with an outlook on how recent advancements in machine learning have the potential to streamline the construction of end-to-end data curation systems and bring data closer to users.
Biography: Theodoros (Theo) Rekatsinas is a Moore Data Postdoctoral Fellow at Stanford working with Christopher Ré; he earned his Ph.D. in Computer Science from the University of Maryland, where he was advised by Amol Deshpande and Lise Getoor. His research interests are in data management, with a focus on data integration, data cleaning, and uncertain data. Theo's work on using quality-aware data integration techniques to forecast the emergence and progression of disease outbreaks received the Best Paper Award at SDM 2015. Theo was awarded the Larry S. Davis Doctoral Dissertation award in 2015.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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MHI CommNetS seminar
Wed, Feb 15, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Marcella M. Gomez, UC Berkeley
Talk Title: Delays in biological networks and feedback design
Series: CommNetS
Abstract: Gene regulatory networks lie at the crux of life and, despite rapidly evolving tools in synthetic biology, our ability to replicate the robustness of these systems remains a challenge. We have not been able to fully understand and, hence, design effective feedback mechanisms. I present work towards said challenge through extensions in control and dynamical systems lending to an effective network design in the presence of delays, an adversarial facet of biology.
In this talk I focus on the role of delays in biological networks. I show how understanding the effects of delays and stochastic processes on gene expression dynamics can be used to design effective controllers for stability. First, I present a stability condition for stochastic linear systems with identically, independently, distributed stochastic delays. In an application to a single gene oscillator, I demonstrate the stabilizing effects of increasing the relative variance of the delay uncertainty. Using the insight gained from this analysis along with inspiration from nature, I present a stabilizing controller for the single gene oscillator based on adding a larger delay in parallel. A generalized delay-based feedback design approach shows this architecture to be near optimal. In summary, through a deeper understanding of the effects of delays on dynamics, I arrive at an effective stabilizing controller in a system with large delays, where traditional methods in controls cannot be used for feedback design.
Biography: Marcella M. Gomez is currently a postdoctoral fellow at the University of California, Berkeley in Electrical Engineering and Computer Science. She received her bachelors from UC Berkeley in 2008 and her PhD from the California Institute of Technology in 2015, both in Mechanical Engineering. Her research interests lie in developing synergistic methods combining control and dynamical systems with synthetic biology for the advancement in understanding and designing of complex genetic networks.
Host: Prof. Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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AME Seminar: Christopher S. Combs
Wed, Feb 15, 2017 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Christopher S. Combs, Research Assistant Professor
Talk Title: Advancement of Non-Intrusive Optical Diagnostics for the Study of Supersonic Aerothermodynamics
Host: USC Department of Aerospace and Mechanical Engineering
More Info: http://ame-www.usc.edu/seminars/2-15-17-combs.shtml
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: USC AME (OHE 430)
Event Link: http://ame-www.usc.edu/seminars/2-15-17-combs.shtml
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CS Colloquium: Rashmi K. Vinayak (UC Berkeley) - Smart redundancy for big-data systems: Theory and Practice
Thu, Feb 16, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rashmi K. Vinayak, UC Berkeley
Talk Title: Smart redundancy for big-data systems: Theory and Practice
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Large-scale distributed storage and caching systems form the foundation of big-data systems. A key scalability challenge in distributed storage systems is achieving fault tolerance in a resource-efficient manner. Towards addressing this challenge, erasure codes provide a storage-efficient alternative to the traditional approach of data replication. However, classical erasure codes come with critical drawbacks: while optimal in utilizing storage space, they significantly increase the usage of other important cluster resources such as network and I/O. In the first part of the talk, I present new erasure codes and theoretical optimality guarantees. The proposed codes reduce the network and I/O usage by 35-70% for typical parameters while retaining the storage efficiency of classical codes. I then present an erasure-coded storage system that employs the proposed codes, and demonstrate significant benefits over the state-of-the-art in evaluations under production setting at Facebook. Our codes have been incorporated into Apache Hadoop 3.0. The second part of the talk focuses on achieving high performance in distributed caching systems. These systems routinely face the challenges of skew in data popularity, background traffic imbalance, and server failures, which result in load imbalance across servers and degradation in read latencies. I present EC-Cache, a cluster cache that employs erasure coding to achieve a 3-5x improvement as compared to the state-of-the-art.
Biography: Rashmi K. Vinayak is a postdoctoral researcher in the EECS department at UC Berkeley, where she received her PhD in 2016. Her dissertation received the Eli Jury Award 2016 from the EECS department at UC Berkeley for outstanding achievement in the area of systems, communications, control, or signal processing. Rashmi is also a recipient of the Facebook Fellowship 2012-13, the Microsoft Research PhD Fellowship 2013-15, and the Google Anita Borg Memorial Scholarship 2015-16. She is also the recipient of the IEEE Data Storage Best Paper and Best Student Paper Awards for the years 2011/2012. Her research interests lie in the theoretical and system challenges that arise in storage and analysis of big data, with a current focus on erasure coding for big-data systems.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Sonny Astani Department Seminar
Fri, Feb 17, 2017 @ 03:00 AM - 03:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ruda Zhang, PhD Student, Sonny Astani Department of Civil and Environmental Engineering
Talk Title: Demand and Supply Distribution of Street Hailing Taxi Service
Abstract: Before the rise of taxi hailing via mobile devices, passengers and taxi drivers have no information about each others' locations. For traditional street hailing taxi services, where are the potential passengers? Where are the free taxis? Does free taxi supply match passenger demand? Using New York City taxi trip records during 2009-2013, we built and tested models to answer these questions.
Host: Roger Ghanem
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Kaela Berry
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AI Seminar - Interview Talk
Fri, Feb 17, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jay Pujara, University of California, Santa Cruz
Talk Title: Probabilistic models for large, noisy, and dynamic data
Abstract: We inhabit a vast, uncertain, and dynamic universe. To succeed in such an environment, artificial intelligence approaches must handle massive amounts of noisy, changing evidence. My research addresses the problems of building scalable, probabilistic models amenable to online updates. To illustrate the potential of such models, I present my work on knowledge graph identification, which jointly resolves the entities, attributes, and relationships in a knowledge graph by combining statistical NLP signals and semantic constraints. Using probabilistic soft logic, a statistical relational learning framework I helped develop, I demonstrate how knowledge graph identification can scale to millions of uncertain candidate facts and tens of millions of semantic dependencies in real-world data while achieving state-of-the-art performance. My work further extends this scalability by adopting a distributed computing approach, reducing the inference time of knowledge graph identification from two hours to ten minutes. Updating large, collective models like those used for knowledge graphs with new information poses a significant challenge. I develop a regret bound for probabilistic models and use this bound to motivate practical algorithms that support low-regret updates while improving inference time over 65%. Finally, I highlight several active projects in sustainability, bioinformatics, and mobile analytics that provide a promising foundation for future research.
Biography: Jay Pujara is a postdoctoral researcher at the University of California, Santa Cruz whose principal areas of research are machine learning, artificial intelligence, and data science. He completed his PhD at the University of Maryland, College Park and received his MS and BS at Carnegie Mellon University. Prior to his PhD, Jay spent six years at Yahoo! working on mail spam detection, user trust, and contextual mail experiences, and he has also worked at Google, LinkedIn and Oracle. Jay is the author of over twenty peer-reviewed publications and has received three best paper awards for his work. He is a recognized authority on knowledge graphs, and has organized the Automatic Knowledge Base Construction (AKBC) workshop, recently presented a tutorial on knowledge graph construction, and has had his work featured in AI Magazine. For more information, visit https://www.jaypujara.org
Host: Craig Knoblock
More Info: http://webcastermshd.isi.edu/Mediasite/Play/1ed0700540864caabaedfc675e89543e1d
Location: Information Science Institute (ISI) -
Audiences: Everyone Is Invited
Contact: Kary LAU
Event Link: http://webcastermshd.isi.edu/Mediasite/Play/1ed0700540864caabaedfc675e89543e1d
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Munushian Keynote Lecture - William E. Moerner, Friday, February 17th at 2:00pm in GER124
Fri, Feb 17, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. William E. Moerner - Nobel Prize in Chemistry, Nobel Foundation (2014), Stanford University
Talk Title: The Story of Photonics and Single Molecules, from Early Spectroscopy in Solids, to Super-Resolution Nanoscopy in Cells and Beyond
Abstract: More than 25 years ago, low temperature experiments aimed at establishing the ultimate limits to optical storage in solids led to the first optical detection and spectroscopy of a single molecule in the condensed phase. At this unexplored ultimate limit, many surprises occurred where single molecules showed both spontaneous changes (blinking) and light-driven control of emission, properties that were also observed in 1997 at room temperature with single green fluorescent protein variants. In 2006, PALM and subsequent approaches showed that the optical diffraction limit of ~200 nm can be circumvented to achieve super-resolution fluorescence microscopy, or nanoscopy, with relatively nonperturbative visible light. Essential to this is the combination of single-molecule fluorescence imaging with active control of the emitting concentration and sequential localization of single fluorophores decorating a structure. Super-resolution microscopy has opened up a new frontier in which biological structures and behavior can be observed in live cells with resolutions down to 20-40 nm and below. Examples range from protein superstructures in bacteria to bands in actin filaments to details of the shapes of amyloid fibrils and much more. Current methods development research addresses ways to extract more information from each single molecule such as 3D position and orientation, and to assure not only precision, but also accuracy. Still, it is worth noting that in spite of all the interest in super-resolution, even in the "conventional" single-molecule tracking regime where the motions of individual biomolecules are recorded in solution or in cells rather than the shapes of extended structures, much can still be learned about biological processes when ensemble averaging is removed.
Biography: William Moerner is an American physical chemist and chemical physicist with current work in the biophysics and imaging of single molecules. He is credited with achieving the first optical detection and spectroscopy of a single molecule in condensed phases, along with his postdoc, Lothar Kador. Optical study of single molecules has subsequently become a widely used single-molecule experiment in chemistry, physics and biology. In 2014 he was awarded the Nobel Prize in Chemistry.
He attended Washington University in St. Louis for undergraduate studies as an Alexander S. Langsdorf Engineering Fellow, and obtained three degrees: a B.S. in physics with Final Honors, a B.S. in electrical engineering with Final Honors, and an A.B. in mathematics summa cum laude in 1975. This was followed by graduate study, partially supported by a National Science Foundation Graduate Fellowship, at Cornell University in the group of Albert J. Sievers III. Here he received an M.S. degree and a Ph.D. degree in physics in 1978 and 1982, respectively.
Host: EE-Electrophysics
More Info: minghsiehee.usc.edu/about/lectures/munushian-lecture
Location: Ethel Percy Andrus Gerontology Center (GER) - 124
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: minghsiehee.usc.edu/about/lectures/munushian-lecture
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Astani Civil and Environmental Engineering Ph.D. Seminar
Fri, Feb 17, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ruda Zhang and Pedram Oskoue , Astani Ph.D. Students
Talk Title: Demand and Supply Distribution of Street Hailing Taxi Service/ In-situ Quality Control of Scan Data for As-built Models
More Information: Astani CEE Ph.D. Seminar Abstract 2-17-2017.pdf.docx
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Sonny Astani Department Seminar
Fri, Feb 17, 2017 @ 03:00 PM - 03:30 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ruda Zhang, PhD Student, Sonny Astani Department of Civil and Environmental Engineering
Talk Title: Demand and Supply Distribution of Street Hailing Taxi Service
Abstract: Before the rise of taxi hailing via mobile devices, passengers and taxi drivers have no information about each others' locations. For traditional street hailing taxi services, where are the potential passengers? Where are the free taxis? Does free taxi supply match passenger demand? Using New York City taxi trip records during 2009-2013, we built and tested models to answer these questions.
Host: Roger Ghanem
More Information: Sonny Astani Department Seminar.pdf
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Kaela Berry
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Seminars in Biomedical Engineering
Mon, Feb 20, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: PRESIDENT'S DAY (NO SEMINAR), PRESIDENT'S DAY (NO SEMINAR)
Talk Title: PRESIDENT'S DAY (NO SEMINAR)
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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USC Stem Cell Seminar: David Scadden, Harvard University
Tue, Feb 21, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: David Scadden, Harvard University
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: Shivaram Venkataraman (UC Berkeley) - Scalable Systems for Fast and Easy Machine Learning
Tue, Feb 21, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Shivaram Venkataraman, UC Berkeley
Talk Title: Scalable Systems for Fast and Easy Machine Learning
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Machine learning models trained on massive datasets power a number of applications; from machine translation to detecting supernovae in astrophysics. However the end of Moore's law and the shift towards distributed computing architectures presents many new challenges for building and executing such applications in a scalable fashion.
In this talk I will present my research on systems that make it easier to develop new machine learning applications and scale them while achieving high performance. I will first present programming models that let users easily build distributed machine learning applications. Next, I will show how we can exploit the structure of machine learning workloads to build low-overhead performance models that can help users understand scalability and simplify large scale deployments. Finally, I will describe scheduling techniques that can improve scalability and achieve high performance when using distributed data processing frameworks.
Biography: Shivaram Venkataraman is a PhD Candidate at the University of California, Berkeley and is advised by Mike Franklin and Ion Stoica. His research interests are in designing systems and algorithms for large scale data processing and machine-learning. He is a recipient of the Siebel Scholarship and best-of-conference citations at VLDB and KDD. Before coming to Berkeley, he completed his M.S at the University of Illinois, Urbana-Champaign.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute Seminar, ISE 651
Tue, Feb 21, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Benjamin Recht , Associate Professor, UC Berkeley
Talk Title: Optimization Challenges in Deep Learning
Host: Dr. Suvrajeet Sen
More Information: February 21, 2017_Recht.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Grace Owh
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Seminars in Biomedical Engineering
Tue, Feb 21, 2017 @ 04:00 PM - 05:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Bruno Olshausen, Ph.D, Professor, Helen Wills Neuroscience Institute and School of Optometry Director, Redwood Center for Theoretical Neuroscience University of California, Berkeley
Talk Title: Neural Computations for Active Perception
Biography: http://redwood.berkeley.edu/bruno/
Host: Bartlett Mel, PhD
More Information: Bruno Olshausen flyer 2.pdf
Location: Hedco Neurosciences Building (HNB) - 100
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
Wed, Feb 22, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sanjit A. Seshia , Professor, University of California, Berkeley
Talk Title: Formal Inductive Synthesis for Cyber-Physical Systems
Abstract: Cyber-physical systems are computational systems tightly integrated with physical processes. Examples include modern automobiles,fly-by-wire aircraft, software-controlled medical devices, robots, and many more. In recent times, these systems have exploded in complexity due to the growing amount of software and networking integrated into physical environments via real-time control loops. At the same time, they typically must be designed with strong verifiable guarantees.
In this talk, I will describe how formal inductive synthesis --- algorithmic synthesis from examples with formal guarantees --- can be brought to bear on some important problems in the modeling, design, and analysis of cyber-physical systems. Both theory and industrial case studies will be discussed, with a special focus on the automotive domain.
Biography: Sanjit A. Seshia is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He received an M.S. and Ph.D. in Computer Science from Carnegie Mellon University, and a B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Bombay. His research interests are in dependable computing and computational logic, with a current focus on applying automated formal methods to problems in cyber-physical systems, computer security, electronic design automation, and synthetic biology. His Ph.D. thesis work on the UCLID verifier and decision procedure helped pioneer the area of satisfiability modulo theories (SMT) and SMT-based verification. He is co-author of a widely-used textbook on embedded systems and has led the development of technologies for cyber-physical systems education based on formal methods. His awards and honors include a Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House, an Alfred P. Sloan Research Fellowship, the Frederick Emmons Terman Award for contributions to electrical engineering and computer science education, and the School of Computer Science Distinguished Dissertation Award at Carnegie Mellon University.
Host: Pierluigi Nuzzo
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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MHI CommNetS seminar
Wed, Feb 22, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ram Vasudevan, University of Michigan
Talk Title: Infinite Dimensional Optimization for Safety Critical Human-in-the-Loop Systems
Series: CommNetS
Abstract: A predominant portion of healthcare spending is devoted to the medical care of unintentional injuries, such as those arising from car accidents or falls. By incorporating automation to predict the likelihood of injury and to design and verify personalized treatment, the burden on healthcare professionals, and thus the overall cost of treatment, can be greatly reduced. Unfortunately, the adoption of automation has been forestalled due to a lack of computationally tractable tools able to identify models of human interaction with the environment and machines, analyze extracted models for perceived threats to determine when aid is required, and synthesize strategies to increase safety in unforeseen circumstances. To address these issues as part of an emerging systems theory for Human-in-the-Loop Systems (HLS), this talk will describe two new techniques each relying upon a new algorithmic framework for infinite dimensional optimization.
The first technique is a provably convergent hybrid optimal control algorithm that can automatically identify an individual-specific model of locomotion. When applied to a nine person motion capture walking experiment, the models identified by the algorithm revealed morphological and neurological pathologies. The second technique is a scalable convex programming approach for simultaneous reachable set computation and personalized controller synthesis for safety critical HLS. For locomotion, this approach determines a likelihood for falling while constructing an optimal feedback control law to reduce the risk of injury. This tool is able to tractable predict those who are greatest risk of falling in a completely non-invasive manner.
Biography: Ram Vasudevan is an assistant professor in Mechanical Engineering at the University of Michigan with appointments in the University of Michigan Transportation Research Institute and the University of Michigan's Robotics Program. He received a BS in Electrical Engineering and Computer Sciences and an Honors Degree in Physics in May 2006, an MS degree in Electrical Engineering in May 2009, and a PhD in Electrical Engineering in December 2012 all from the University of California, Berkeley. Subsequently, he worked as a postdoctoral associate in the Locomotion Group at MIT from 2012 till 2014 before joining the University of Michigan in 2015. His research interests include dynamical systems, optimization, and robotics especially to applications involving human interaction with Cyber Physical Systems.
Host: Prof. Insoon Yang
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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Lyman Handy Colloquia
Thu, Feb 23, 2017 @ 12:45 AM - 01:50 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Dr. Arvind Varma, Purdue University
Talk Title: Selected Topics Related to Energy and Chemicals
Host: Dr. Theodore Tsotsis
Location: James H. Zumberge Hall Of Science (ZHS) - 159
Audiences: Everyone Is Invited
Contact: Aleessa Atienza
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CS Colloquium: Xiang Ren (UIUC) - Effort-Light StructMine: Turning Massive Corpora into Structures
Thu, Feb 23, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Xiang Ren, UIUC
Talk Title: Effort-Light StructMine: Turning Massive Corpora into Structures
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
The real-world data, though massive, are hard for machines to resolve as they are largely unstructured and in the form of natural-language text. One of the grand challenges is to turn such massive corpora into machine-actionable structures. Yet, most existing systems have heavy reliance on human effort in the process of structuring various corpora, slowing down the development of downstream applications.
In this talk, I will introduce a data-driven framework, Effort-Light StructMine, that extracts structured facts from massive corpora without explicit human labeling effort. In particular, I will discuss how to solve three StructMine tasks under Effort-Light StructMine framework: from identifying typed entities in text, to fine-grained entity typing, to extracting typed relationships between entities. Together, these three solutions form a clear roadmap for turning a massive corpus into a structured network to represent its factual knowledge. Finally, I will share some directions towards mining corpus-specific structured networks for knowledge discovery.
Biography: Xiang Ren is a Computer Science PhD candidate at University of Illinois at Urbana-Champaign, working with Jiawei Han and the Data and Information System ï¼DAISï¼Research Lab. Xiang's research develops data-driven methods for turning unstructured text data into machine-actionable structures. More broadly, his research interests span data mining, machine learning, and natural language processing, with a focus on making sense of massive text corpora. His research has been recognized with a Google PhD Fellowship, Yahoo!-DAIS Research Excellence Award, C. W. Gear Outstanding Graduate Student Award, and has been transferred to US Army Research Lab, NIH, Microsoft, Yelp and TripAdvisor.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Feb 24, 2017 @ 02:30 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yuanxun Ethan Wang, Professor at UCLA
Talk Title: Time-Varying Electromagnetic Devices: Breaking the Fundamental Limits of Passives
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Yuanxun Ethan 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, Feb 24, 2017 @ 03:00 PM - 04:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Mario Berges, Dept. of Civil and Environmental Engineering, Carnegie Mellon University
Talk Title: Towards Autonomous Urban Infrastructure: Why and How
Abstract: Abstract
The worldwide growth of urban population, climate change and resource constraints are driving a rethinking of the way we design, construct and operate the civil infrastructure that supports our cities, both new and old. Concurrently, recent advances in sensing and communication are allowing us to peer into urban phenomena and infrastructure in a dramatically different way. However, cost-effective and scalable solutions for these so-called "smart cities" remain challenging. In this talk, I will describe recent efforts by my group and colleagues at Carnegie Mellon University to address these scalability challenges through novel applications of sensing and machine learning. In particular, I will focus on indirect sensing techniques that allow us to extract granular information about infrastructure conditions at a reduced instrumentation/labor cost and describe two research projects in this domain: one on electricity demand disaggregation, and one on structural health monitoring.
Biography: Dr. Mario Bergés is an Associate Professor, at the Department of Civil and Environmental Engineering, at Carnegie Mellon University. Bergés studied under USC Sonny Astani Department Chair Lucio Soibelman when receiving his PhD at Carnegied Mellon University. His research interests are in making our built environment more operationally efficient and robust through the use of information technologies, so that it can better deal with future resource constraints and a changing environment. In other words, his interests lie in providing buildings, and otherman-made structures that support our urban environment, with the ability to sense, plan and act autonomously, just as many living organisms do.
More Information: CEE Seminar_ Dr. Mario Berges.pdf
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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CS Colloquium: Ellie Pavlick (University of Pennsylvania) - Natural Language Understanding with Paraphrases and Composition
Mon, Feb 27, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ellie Pavlick, University of Pennsylvania
Talk Title: Natural Language Understanding with Paraphrases and Composition
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Natural language processing (NLP) aims to teach computers to understand human language. NLP has enabled some of the most visible applications of artificial intelligence, including Google search, IBM Watson, and Apple's Siri. As AI is applied to increasingly complex domains such as health care, education, and government, NLP will play a crucial role in allowing computational systems to access the vast amount of human knowledge documented in the form of unstructured speech and text.
In this talk, I will discuss my work on training computers to make inferences about what is true or false based on information expressed in natural language. My approach combines machine learning with insights from formal linguistics in order to build data-driven models of semantics which are more precise and interpretable than would be possible using linguistically naive approaches. I will begin with my work on automatically adding semantic annotations to the 100 million phrase pairs in the Paraphrase Database (PPDB). These annotations provide the type of information necessary for carrying out precise inferences in natural language, transforming the database into a largest available lexical semantics resource for natural language processing. I will then turn to the problem of compositional entailment, and present an algorithm for performing inferences about long phrases which are unlikely to have been observed in data. Finally, I will discuss my current work on pragmatic reasoning: when and how humans derive meaning from a sentence beyond what is literally contained in the words. I will describe the difficulties that such "common-sense" inference poses for automatic language understanding, and present my on-going work on models for overcoming these challenges.
Biography: Ellie Pavlick is a PhD student at the University of Pennsylvania, advised by Dr. Chris Callison-Burch. Her dissertation focuses on natural language inference and entailment. Outside of her dissertation research, Ellie has published work on stylistic variation in paraphrase--e.g. how paraphrases can effect the formality or the complexity of language--and on applications of crowdsourcing to natural language processing and social science problems. She has been involved in the design and instruction of Penn's first undergraduate course on Crowdsourcing and Human Computation (NETS 213). Ellie is a 2016 Facebook PhD Fellow, and has interned at Google Research, Yahoo Labs, and the Allen Institute for Artificial Intelligence.
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, Feb 27, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Mahnaz Shahidi, PhD, Professor of Ophthalmology and Biomedical Engineering Riffenburgh Professor in Glaucoma Vice Chair for Translational Research Department of Ophthalmology University of Southern California
Talk Title: Multimodal Imaging of Retinal Oxygen Delivery and Metabolism
Abstract: Retinal tissue function can be adversely affected by inadequate delivery and/or consumption of oxygen. In fact, derangements in retinal oxygenation are thought to contribute significantly to the development of common vision threatening retinal diseases. However, mechanisms that implicate oxygen in the development of retinal pathologies and impairment of retinal function are not completely understood. Therefore, technologies that allow assessment of oxygen tension in the retinal vasculature and tissue are needed to broaden knowledge of disease pathophysiology, and thereby advance diagnostic and therapeutic procedures. We have developed an optical section phosphorescence lifetime imaging technique that allows depth-resolved mapping of retinal vascular oxygen tension and measurement of inner retinal oxygen extraction fraction. Combined with fluorescent microsphere imaging for measurement of retinal blood flow, oxygen delivery by the retinal circulation and global inner retinal oxygen metabolism are derived. These technologies have been applied for assessment of retinal oxygen delivery and metabolism in experimental animal models of retinal ischemia.
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, Feb 27, 2017 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Geir E. Dullerud, Professor, University of Illinois at Urbana-Champaign
Talk Title: Statistical Validation and Principle-Based Simulation of Complex Cyber-Controlled Systems
Abstract: The talk will focus on simulation and a computational approach to verification of the hybrid mathematical models that are formed when combining physics-based models with discrete-transition models, such as those which model software algorithms. Namely, the mathematical models that arise when for instance considering Cyberphysical Systems, or the Internet of Things.
In many game theory and filtering problems it is not possible to analytically obtain solutions for statistical properties of systems under study, and in the first part of the talk we will describe our recent work on numerical approaches to obtaining estimates of these properties, and the application of the techniques developed to particle filtering. Monte Carlo simulation of Markov processes allows the numerical estimation of their statistical properties from an ensemble of sample system paths. We present methods for generating reduced-variance path ensembles for the tau-leaping discrete-time simulation algorithm, which allows mean stochastic process dynamics to be estimated with substantially smaller ensemble sizes. Our methods are based on antithetic and stratified sampling of Poisson random variates, and we provide a combination of analytical proofs and numerical evidence for their performance, which can frequently be a 2-3 orders of magnitude improvement over standard Monte Carlo. Application examples will be discussed.
The second part of the talk will concentrate on system verification, and will present a new verification algorithm for continuous-time stochastic hybrid systems, whose specifications are expressed in metric interval temporal logic (MITL), by deploying a novel model reduction method. By partitioning the state space of the hybrid system and computing the optimal transition rates between partitions, we provide a procedure to both reduce the system to a continuous-time Markov chain, and the associated specification formulas. We prove that the unreduced formulas hold (or do not) if the corresponding reduced formula on the Markov chain is robustly true (or false) under certain perturbations. In addition, a stochastic algorithm to complete the verification has been developed. We have extended the approach of this algorithm, and have developed a direct stochastic algorithm for probabilistically verifying a certain hybrid system class, and applied this technique to an extensive benchmark problem with realistic dynamics.
Biography: Geir E. Dullerud is the W. Grafton and Lillian B. Wilkins Professor in Mechanical Engineering at the University of Illinois at Urbana-Champaign. There he is also a member of the Coordinated Science Laboratory, where he is Director of the Decision and Control Laboratory (21 faculty); he is an Affiliate Professor of both Computer Science, and Electrical and Computer Engineering. He has held visiting positions in Electrical Engineering KTH, Stockholm (2013), and Aeronautics and Astronautics, Stanford University (2005-2006). Earlier he was on faculty in Applied Mathematics at the University of Waterloo (1996-1998), after being a Research Fellow at the California Institute of Technology (1994-1995), in the Control and Dynamical Systems Department. He has published two books: "A Course in Robust Control Theory", Texts in Applied Mathematics, Springer, 2000, and "Control of Uncertain Sampled-data Systems", Birkhauser 1996. His areas of current research interest include convex optimization in control, cyber-physical system security, cooperative robotics, stochastic simulation, and hybrid dynamical systems. In 1999 he received the CAREER Award from the National Science Foundation, and in 2005 the Xerox Faculty Research Award at UIUC. He is a Fellow of both IEEE (2008) and ASME (2011).
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Estela Lopez
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CAIS Seminar Series: Dr. Pascal Van Hentenryck (University of Michigan) - The Case of Infrastructure Optimization
Mon, Feb 27, 2017 @ 04:00 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Pascal Van Hentenryck, University of Michigan
Talk Title: The Case of Infrastructure Optimization
Series: Center for AI in Society (CAIS) Seminar Series
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
In the last decade, massive amount of information has been collected about critical infrastructures, including the transportation network and the electrical power system. These data sets, together with progress in Artificial Intelligence and Operations Research, make it possible to analyze, predict, and optimize these infrastructures with unprecedented fidelity. This talk demonstrates the societal benefits of this transformation on a number of case studies in evacuation planning, public transportation, and power restoration.
Biography: Dr. Pascal Van Hentenryck is the Seth Bonder Collegiate Professor of Engineering at the University of Michigan. He is Professor of Industrial and Operations Engineering, Professor of Electrical Engineering and Computer Science, and core faculty in the Michigan Institute of Data Science. He is the author of the pioneering CHIP and OPL optimization systems, which have been widely used in academia and industry. Dr. Van Hentenryck is the author of five MIT Press books and is a fellow of AAAI and INFORMS.
Host: Milind Tambe
Location: John Stauffer Science Lecture Hall (SLH) - 100
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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USC Stem Cell Seminar: Michael Rudnicki, Ottawa Hospital Research Institute
Tue, Feb 28, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Michael Rudnicki, Ottawa Hospital Research Institute
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: Vinodkumar Prabhakaran (Stanford University) - NLP for Social Good: Inferring Social Context from Language
Tue, Feb 28, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Vinodkumar Prabhakaran, Stanford University
Talk Title: NLP for Social Good: Inferring Social Context from Language
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
The vast quantities of language data online and offline offer tremendous opportunities to study society through language. In this talk, I show how natural language processing techniques can be expanded from understanding the meanings of words and sentences, to inferring the underlying social structures and processes they reflect and identifying crucial shortcomings in them. I apply these techniques to computationally detect two ways in which the social context affects the use of language: social relations affecting how people interact with one another, and social constructs shaping how institutions interact with communities. In the first part, I show how to computationally detect manifestations of social power in workplace interactions between individuals -” providing means for organizations to detect incivility at workplace. In the second part, I show how to computationally investigate the ways race shapes the interactions between the police and the communities they serve -” providing means for departments to address and monitor racial disparities in policing. My research looks beyond words and phrases, and introduce ways to infer richer rhetorical and dialog information like conversational structure and respect that reflect the social context, demonstrating the importance of deeper language processing for the computational social sciences.
Biography: Vinodkumar Prabhakaran is a postdoctoral fellow in the computer science department at Stanford University. His research falls in the inter-disciplinary field of computational sociolinguistics, in which he builds and uses computational tools to analyze linguistic patterns that reveal the underlying social contexts in which language is used. He received his PhD in Computer Science from Columbia University in 2015. In his doctoral thesis, he studied how machine learning and natural language processing techniques can help detect the underlying social power structures that guide social interactions. As part of his research, he has also made significant contributions to core NLP problems such as extracting information from text, as well as modeling structures of dialog and discourse.
Host: CS Department
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute Seminar, ISE 651
Tue, Feb 28, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Mariel Lavieri , Associate Professor, University of Michigan
Talk Title: Personalizing Management of Glaucoma Patients
Host: Dr. Sze-chuan Suen
More Information: February 28, 2017_Lavieri.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium: Fan Long (MIT CSAIL) - Learning How to Patch Software Errors Automatically
Tue, Feb 28, 2017 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Fan Long, MIT CSAIL
Talk Title: Learning How to Patch Software Errors Automatically
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Software systems are increasingly integrated into every part of our society. As the number of systems and our dependence on these systems continue to grow, making these systems reliable and secure becomes an increasingly important challenge for our society and a daunting task for software developers.
Automatic patch generation holds out the promise of automatically correcting software defects without the need for developers to manually diagnose, understand, and correct these defects. In this talk, I will present two novel automatic patch generation systems, Prophet and Genesis, both of which learn from past successful human patches to automatically fix defects. By collectively leveraging development efforts worldwide, Prophet and Genesis automatically generate correct patches for real-world defects in large open-source C and Java applications with up to millions lines of code. This research also demonstrates that the growing volume of software programs is not just a challenge but also a great opportunity. Exploiting this opportunity can enable revolutionary new automated techniques that enhance software reliability and security.
Biography: Fan Long is a PhD candidate in Computer Science at Massachusetts Institute of Technology (MIT). His research to date has focused on developing automated programming systems to improve software reliability and security. He has developed systems that automatically identify and eliminate errors in large software programs and systems that enable software programs to operate successfully in spite of the presence of errors. He holds a BE from Tsinghua University and a MS from MIT.
Host: CS Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
