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Events for April 12, 2017

  • Big Data & Human Behavior Seminar Series: Justin Grimmer (Stanford University) - Exploratory and Confirmatory Causal Inference for High Dimensional Interventions

    Wed, Apr 12, 2017 @ 12:00 PM - 01:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Justin Grimmer, Associate Professor of Political Science and Computer Science, Stanford University

    Talk Title: Exploratory and Confirmatory Causal Inference for High Dimensional Interventions

    Series: Big Data & Human Behavior Seminar Series

    Abstract: An extensive literature in computational social science examines how features of messages, advertisements, and other corpora affect individuals' decisions, but these analyses must specify the relevant features of the text before the experiment. Automated text analysis methods are able to discover features of text, but these methods cannot be used to obtain the estimates of causal effects-”the quantity of interest for applied researchers. We introduce a new experimental design and statistical model to simultaneously discover treatments in a corpora and estimate causal effects for these discovered treatments. We prove the conditions to identify the treatment effects of texts and introduce the supervised Indian Buffet process to discover those treatments. Our method enables us to discover treatments in a training set using a collection of texts and individuals' responses to those texts, and then estimate the effects of these interventions in a test set of new texts and survey respondents. We apply the model to an experiment about candidate biographies, recovering intuitive features of voters' decisions and revealing a penalty for lawyers and a bonus for military service.

    Biography: Justin Grimmer's research examines how representation occurs in American politics using new statistical methods. His first book Representational Style in Congress: What Legislators Say and Why It Matters (Cambridge University Press, 2013) shows how senators define the type of representation they provide constituents and how this affects constituents' evaluations and won the Fenno Prize from the legislative studies section. His second book The Impression of Influence: How Legislator Communication and Government Spending Cultivate a Personal Vote (Princeton University Press, with Sean J. Westwood and Solomon Messing) demonstrates how legislators ensure they receive credit for government actions. His work has appeared in the American Political Science Review, American Journal of Political Science, Journal of Politics, Political Analysis, Proceedings of the National Academy of Sciences, Regulation and Governance, and other journals.

    Host: Morteza Dehghani

    Location: BCI

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • MHI CommNetS Seminar

    Wed, Apr 12, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Ian M. Mitchell, University of British Columbia

    Talk Title: Using model checking verifications online: Handling runtime state uncertainty, human-in-the-loop shared control and sampled data feedback

    Series: CommNetS

    Abstract: Recent advances in model checking algorithms for continuous state systems allow us to demonstrate the existence of safe control policies robust to model error for cyber-physical systems (CPS) of practical interest, such as shared control drones or wheelchairs, or automated delivery of anesthesia. However, these verification results are only relevant if we can implement those policies. In this talk I will discuss investigations into three challenges that arise when it comes time to synthesize a feedback control signal that will keep the system safe: Online state uncertainty, human-in-the-loop shared control for older adults with cognitive impairment, and the sampled data nature of that feedback control in typical cyber-physical systems.

    Biography: Ian M. Mitchell completed his doctoral work in engineering at Stanford University in 2002, spent a year as a postdoctoral researcher at the University of California at Berkeley, and is now an Associate Professor of Computer Science at the University of British Columbia. He is the author of the Toolbox of Level Set Methods, the first publicly available high accuracy implementation of solvers for dynamic implicit surfaces and the time dependent Hamilton-Jacobi equation that works in arbitrary dimension. His research interests include development of algorithms and software for nonlinear differential equations, formal verification, control and planning in cyber-physical and robotic systems, assistive technology and reproducible research.

    Host: Prof. Insoon Yang

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Posted By: Annie Yu

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  • Aerospace & Mechanical Engineering Seminar

    Wed, Apr 12, 2017 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jeff Eldredge, Professor, Mechanical & Aerospace Engineering Department, University of California at Los Angeles

    Talk Title: Low-Order Modeling of Agile Flight

    Abstract: The highly agile flight exhibited by many flying creatures has, for many years, been the promise for the next generation of flight vehicles. However, the reality still falls short, in part because such agility requires flight control strategies that work robustly in the regime of separated flows. This regime, generally avoided by human-engineered vehicles, is often exploited by airborne creatures in order to make rapid maneuvers or maintain tolerance to gusts. Recent control strategies based on flapping wings or managed separation over fixed wings have shown promise, but are limited to slow maneuvers because they rely on linearized and/or quasi-steady models of the aerodynamics, only effective at low frequencies or averaged over many flapping cycles. In this presentation, I will report on our recent progress in developing unsteady non-linear (vortex-based) models of separated flows. The premise is to construct a low-degree-of-freedom template model, with the simplest description of the flow that still contains the non-linear vortex-vortex and vortex-wing interactions. The model is then closed with empirical data from sensors. I will demonstrate progress on several canonical problems in two dimensions, and discuss our extensions to fully three-dimensional flows. I will also highlight some future directions of the work.

    Biography: Jeff Eldredge is a Professor in the Mechanical & Aerospace Engineering Department at UCLA. His research interests are in computational and theoretical studies of problems in fluid dynamics, including those in unsteady aerodynamics, bio-inspired locomotion, micro-particle manipulation, and biomedical and physiological flows. He has received the NSF CAREER Award and is an Associate Fellow of AIAA. Prior to starting at UCLA, Prof. Eldredge was a research associate at the University of Cambridge. He received his M.S and Ph.D. at Caltech and his B.S. at Cornell, all in mechanical engineering.

    Host: Department of Aerospace and Mechanical Engineering

    More Info: https://ame.usc.edu/about/seminars/

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Posted By: Ashleen Knutsen

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