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Events for March 27, 2017

  • CS Colloquium: David Held (UC Berkeley) - Robots in Clutter: Learning to Understand Environmental Changes

    Mon, Mar 27, 2017 @ 11:00 AM - 12:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: David Held, UC Berkeley

    Talk Title: Robots in Clutter: Learning to Understand Environmental Changes

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    Robots today are confined to operate in relatively simple, controlled environments. One reason for this is that current methods for processing visual data tend to break down when faced with occlusions, viewpoint changes, poor lighting, and other challenging but common situations that occur when robots are placed in the real world. I will show that we can train robots to handle these variations by modeling the causes behind visual appearance changes. If robots can learn how the world changes over time, they can be robust to the types of changes that objects often undergo. I demonstrate this idea in the context of autonomous driving, and I will show how we can use this idea to improve performance for every step of the robotic perception pipeline: object segmentation, tracking, and velocity estimation. I will also present some recent work on learning to manipulate objects, using a similar framework of learning environmental changes. By learning how the environment can change over time, we can enable robots to operate in the complex, cluttered environments of our daily lives.

    Biography: David Held is a post-doctoral researcher at U.C. Berkeley working with Pieter Abbeel on deep reinforcement learning for robotics. He recently completed his Ph.D. in Computer Science at Stanford University with Sebastian Thrun and Silvio Savarese, where he developed methods for perception for autonomous vehicles. David has also worked as an intern on Google's self-driving car team. Before Stanford, David was a researcher at the Weizmann Institute, where he worked on building a robotic octopus. He received a B.S. and M.S. in Mechanical Engineering at MIT and an M.S. in Computer Science at Stanford, for which he was awarded the Best Master's Thesis Award from the Computer Science Department.

    Host: CS Department

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Seminars in Biomedical Engineering

    Mon, Mar 27, 2017 @ 12:30 PM - 01:50 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jean-Michel Maarek, PhD, Professor of Engineering Practice, USC Biomedical Engineering

    Talk Title: Flexible Devices

    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Posted By: 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, Mar 27, 2017 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Massimo Franceschetti, Professor, University of California San Diego

    Talk Title: The value of information in event triggering: can we beat the data-rate theorem?

    Abstract: In networked control, data-rate theorems relate the amount of information that the feedback channel between estimator and controller must be able to supply to guarantee stability, to the amount of information requested by the plant. They represent a cornerstone of the theory of cyber-physical systems (CPS) and have been studied for more than a decade. On the other hand, the need to use distributed resources efficiently in CPS has led to event-triggering control techniques based on the idea of sending information in an opportunistic manner between the controller and the plant. After reviewing the basics of the data rate theorems, we illustrate how these are to be modified in the presence of an event-triggered implementation. The main observation is that the act of triggering reveals information about the system's state and can be exploited for stabilization, thus effectively invalidating "classic" formulations of the theorem. An extended formulation reveals a phase transition behavior of the transmission rate required for stabilization as a function of the communication delay. It is shown that for low values of the delay the timing information carried by the triggering events is large and the system can be stabilized with any positive rate. On the other hand, when the delay exceeds a certain threshold that depends on the given triggering strategy, the timing information alone is not enough to achieve stabilization and the rate must begin to grow, eventually becoming larger than what required by the classic data-rate theorem. The critical point where the transmission rate equals the one imposed by the data-rate theorem occurs when the delay equals the inverse of the entropy rate of the plant, representing the intrinsic rate at which the system generates information. At this critical point, the timing information supplied by event triggering is completely balanced by the information loss due to the communication delay.

    Biography: Massimo Franceschetti received the Laurea degree (with highest honors) in computer engineering from the University of Naples, Naples, Italy, in 1997, the M.S. and Ph.D. degrees in electrical engineering from the California Institute of Technology, Pasadena, CA, in 1999, and 2003, respectively. He is Professor of Electrical and Computer Engineering at the University of California at San Diego (UCSD). Before joining UCSD, he was a postdoctoral scholar at the University of California at Berkeley for two years. He has held visiting positions at the Vrije Universiteit Amsterdam, the Ecole Polytechnique Federale de Lausanne, and the University of Trento. His research interests are in physical and information-based foundations of communication and control systems. He is co-author of the book "Random Networks for Communication" published by Cambridge University Press. Dr. Franceschetti served as Associate Editor for the IEEE Transactions on Information Theory (2009-2012) and for the IEEE Transactions on Control of Network Systems (2013-16) and as Guest Associate Editor of the IEEE Journal on Selected Areas in Communications (2008, 2009). He is currently serving as Associate Editor of the IEEE Transactions on Network Science and Engineering. He was awarded the C. H. Wilts Prize in 2003 for best doctoral thesis in electrical engineering at Caltech, the S.A. Schelkunoff Award in 2005 for best paper in the IEEE Transactions on Antennas and Propagation, a National Science Foundation (NSF) CAREER award in 2006, an Office of Naval Research (ONR) Young Investigator Award in 2007, the IEEE Communications Society Best Tutorial Paper Award in 2010, and the IEEE Control theory society Ruberti young researcher award in 2012.

    Host: Paul Bogdan

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Estela Lopez

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  • NL Seminar - ANALYZING THE LANGUAGE OF FOOD ON SOCIAL MEDIA

    Mon, Mar 27, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Stephen Kobourov , University of Arizona

    Talk Title: ANALYZING THE LANGUAGE OF FOOD ON SOCIAL MEDIA

    Series: Natural Language Seminar

    Abstract: We investigate the predictive power behind the language of food on social media. We collect a corpus of over three million food-related posts from Twitter and demonstrate that many latent population characteristics can be directly predicted from this data: overweight rate, diabetes rate, political leaning, and home geographical location of authors. For all tasks, our language-based models significantly outperform the majority class baselines. Performance is further improved with more complex natural language processing, such as topic modeling. We analyze which textual features have most predictive power for these datasets, providing insight into the connections between the language of food, geographic locale, and community characteristics. Lastly, we design and implement an online system for real-time query and visualization of the dataset. Visualization tools, such as geo referenced heatmaps, semantics-preserving wordclouds and temporal histograms, allow us to discover more complex, global patterns mirrored in the language of food.


    Biography: Stephen Kobourov is a Professor of Computer Science at the University of Arizona. He completed BS degrees in Mathematics and Computer Science at Dartmouth College in 1995, and a PhD in Computer Science at Johns Hopkins University in 2000. He has worked as a Research Scientist at AT&T Research Labs, a Hulmboldt Fellow at the University of Tubingen in Germany, and a Distinguished Fulbright Chair at Charles University in Prague.

    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

    Posted By: Peter Zamar

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