Institute for Computational and Mathematical Engineering (ICME)
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Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering
BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His research focuses on understanding how an agent interacting with a poorly understood environment can learn over time to make effective decisions. He is interested in the design of efficient reinforcement learning algorithms, understanding what is possible or impossible in this domain, and applying the technology toward the benefit of society. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edits the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization.
He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, and the Management Science and Engineering Department's Graduate Teaching Award. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen.
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
Current Research and Scholarly InterestsMy research focus is in deep learning for medical image analysis.
During Masters, my research was in best rank-1 approximations in the 1-norm.
Robert Grimmett Professor in Mathematics
Current Research and Scholarly InterestsMy research concentrates on topics in two broad areas of applications of microlocal analysis in which, partly with collaborators, I introduced new ideas in recent years: non-elliptic linear and non-linear partial differential equations (PDE), typically concerning wave propagation or other related phenomena, and inverse problems for X-ray type transforms along geodesics and related problems for determining the metric tensor from boundary measurements.