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Events for February 26, 2019
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CS Colloquium: Rajalakshmi Nandakumar (University of Washington) - Computational Wireless Sensing at Scale
Tue, Feb 26, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rajalakshmi Nandakumar, University of Washington
Talk Title: Computational Wireless Sensing at Scale
Series: CS Colloquium
Abstract: Computational wireless sensing is an exciting field of research where we use wireless signals from everyday computing devices to enable sensing. The key challenge is to enable new sensing capabilities that can be deployed at scale and have an impact in the real world.
In this talk, I will focus on the two unique approaches that I pursued to enable sensing at scale. The first is to transform existing smart devices such as smartphones into active sonar systems to enable mobile health and user interaction applications. In particular, I will talk about contactless sensing of physiological signals like breathing using off-the-shelf smartphones that can be used to detect potentially life-threatening conditions such as opioid overdoses as well as sleep apnea. The second approach is to design new low power wireless technologies that can enable IoT sensing on everyday objects on a large scale by addressing power and size constraints. Here, I will talk about our technology that achieves 3D localization and tracking of sub-centimeter sized devices that enables applications ranging from user interaction to precision agriculture.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Rajalakshmi Nandakumar is a Ph.D. candidate at the Paul G. Allen School of computer science of University of Washington. Her research focuses on developing wireless sensing technologies that enable novel applications in various domains including mobile health, user interfaces and IoT networks. She developed the first contactless smartphone based sleep apnea diagnosis system that was licensed by ResMed Inc. and now used by millions of users for sleep staging. She was recognized with the Paul Baran Young Scholar award by the Marconi Society in 2018 and also named as the rising star in EECS by MIT. She has first author papers in top medical journals including Science translational medicine as well as computer science venues (CHI, SIGCOMM, SenSys, MobiCom, MobiSys). Her research was awarded multiple accolades and nominations including MobiSys 2015 best paper nominee, CHI 2016 Honorable mention award and SenSys 2018 best paper award.
Host: Ramesh Govindan
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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MASCLE Machine Learning Seminar: Jacob Abernethy (Georgia Tech) - Building Algorithms by Playing Games
Tue, Feb 26, 2019 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jacob Abernethy, Georgia Institute of Technology
Talk Title: Building Algorithms by Playing Games
Series: Visa Research Machine Learning Seminar Series hosted by USC Machine Learning Center
Abstract: A very popular trick for solving certain types of optimization problems is this: write your objective as the solution of a two-player zero-sum game, endow both players with an appropriate learning algorithm, watch how the opponents compete, and extract an (approximate) solution from the actions/decisions taken by the players throughout the process. This approach is very generic and provides a natural template to produce new and interesting algorithms. I will describe this framework and show how it applies in several scenarios, and describe recent work that draws a connection to the Frank-Wolfe algorithm and Nesterov's Accelerated Gradient Descent.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Jacob Abernethy is an Assistant Professor in Computer Science at Georgia Tech. He started his faculty career in the Department of Electrical Engineering and Computer Science at the University of Michigan. In October 2011 he finished a PhD in the Division of Computer Science at the University of California at Berkeley, and then spent nearly two years as a Simons postdoctoral fellow at the CIS department at UPenn. Abernethy's primary interest is in Machine Learning, with a particular focus in sequential decision making, online learning, online algorithms and adversarial learning models.
Host: Haipeng Luo
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
