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Events for November 29, 2016

  • USC Stem Cell Seminar: Michael Elowitz, California Institute of Technology

    USC Stem Cell Seminar: Michael Elowitz, California Institute of Technology

    Tue, Nov 29, 2016 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Michael Elowitz, California Institute of Technology

    Talk Title: TBD

    Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series

    Host: USC Stem Cell

    More Info: http://stemcell.usc.edu/events

    Webcast: http://keckmedia.usc.edu/Mediasite/Catalog/catalogs/StemCellSeminar

    Location: Eli & Edythe Broad CIRM Center for Regenerative Medicine & Stem Cell Resch. (BCC) - First Floor Conference Room

    WebCast Link: http://keckmedia.usc.edu/Mediasite/Catalog/catalogs/StemCellSeminar

    Audiences: Everyone Is Invited

    Contact: Cristy Lytal/USC Stem Cell

    Event Link: http://stemcell.usc.edu/events

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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

    Tue, Nov 29, 2016 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Partha Pratim Pande, Professor, Washington State University

    Talk Title: Bringing Cores Closer Together: The Wireless Revolution in On-Chip Communication

    Abstract: The continuing progress and integration levels in silicon technologies make complete end-user systems on a single chip possible. This massive level of integration makes modern manycore chips all pervasive in domains ranging from weather forecasting, astronomical data analysis, and biological applications to consumer electronics and smart phones. Network-on-Chips (NoCs) have emerged as communication backbones to enable a high degree of integration in manycore platforms. Despite their advantages, an important performance limitation in traditional NoCs arises from planar metal interconnect-based multi-hop communications, wherein the data transfer between far-apart blocks causes high latency and power consumption. The latency, power consumption, and interconnect routing problems of NoCs can be simultaneously addressed by replacing multi-hop wired paths with high-bandwidth single-hop long-range wireless links. In this talk, we will present design of the millimeter (mm)-wave wireless NoC architectures. We will present detailed performance evaluation and necessary design trade-offs for the small-world network-enabled wireless NoCs with respect to their conventional wireline counterparts in presence of both conventional CMP and emerging big data workloads. We will discuss how Machine Learning can be exploited to design energy efficient Wireless NoC architectures. We will finish this presentation by discussing how the wireless NoC paradigm can enable realization of datacenter-on-chip using heterogeneous processing cores.

    Biography: Partha Pratim Pande is a Professor and holder of the Boeing Centennial Chair in computer engineering at the school of Electrical Engineering and Computer Science, Washington State University, Pullman, USA. His current research interests are novel interconnect architectures for manycore chips, on-chip wireless communication networks, and hardware accelerators for biocomputing. Dr. Pande currently serves as the Editor-in-Chief (EIC) of IEEE Transactions on Multi-Scale Computing Systems (TMSCS) and Associate Editor-in-Chief (A-EIC) of IEEE Design and Test (D&T). He is on the editorial boards of IEEE Transactions on VLSI (TVLSI), ACM Journal of Emerging Technologies in Computing Systems (JETC). He was the technical program committee chair of IEEE/ACM Network-on-Chip Symposium 2015. He also serves in the program committee of many reputed international conferences. He has won the NSF CAREER award in 2009. He is the winner of the Anjan Bose outstanding researcher award from the college of engineering, Washington State University in 2013.

    Host: Paul Bogdan

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

    Audiences: Everyone Is Invited

    Contact: Estela Lopez

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  • Epstein Institute Seminar

    Tue, Nov 29, 2016 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Benjamin F. Hobbs, John Hopkins University

    Talk Title: How Can We Use Optimization to Design Electric Power Markets to Support Socially Optimal Decisions

    Host: Dr. Jong-shi Pang

    More Information: November 29, 2016_Hobbs.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Contact: Michele ISE

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  • CS Colloquium: Richard Samworth (University of Cambridge) - High-dimensional changepoint estimation via sparse projection

    Tue, Nov 29, 2016 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Richard Samworth, University of Cambridge

    Talk Title: High-dimensional changepoint estimation via sparse projection

    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.

    Changepoints are a very common feature of Big Data that arrive in the form of a data stream. We study high-dimensional time series in which, at certain time points, the mean structure changes in a sparse subset of the coordinates. The challenge is to borrow strength across the coordinates in order to detect smaller changes than could be observed in any individual component series. We propose a two-stage procedure called 'inspect' for estimation of the changepoints: first, we argue that a good projection direction can be obtained as the leading left singular vector of the matrix that solves a convex optimisation problem derived from the CUSUM transformation of the time series. We then apply an existing univariate changepoint detection algorithm to the projected series. Our theory provides strong guarantees on both the number of estimated changepoints and the rates of convergence of their locations, and our numerical studies validate its highly competitive empirical performance for a wide range of data generating mechanisms.

    Biography: I am a Professor of Statistics in the Statistical Laboratory, a sub-department of the Department of Pure Mathematics and Mathematical Statistics. This is part of the Faculty of Mathematics at the University of Cambridge. I am also a Teaching Fellow at St John's College, and run the Statistics Clinic for members of the university.

    I currently hold a five-year EPSRC Early Career Fellowship, which began on 1 December 2012. I am also an Alan Turing Institute Faculty Fellow.

    Host: Yan Liu

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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