Lei Ying received his B.E. degree from Tsinghua University, Beijing, China, and his M.S. and Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. He currently is a Professor at the Electrical Engineering and Computer Science Department of the University of Michigan, Ann Arbor, an IEEE Fellow, an Editor-at-Large for the IEEE/ACM Transactions on Networking, and an Associate Editor for the Elsevier Performance Evaluation.
His research is broadly in the interplay of complex stochastic systems and big data, including reinforcement learning, large-scale communication/computing systems for big-data processing, private data marketplaces, and large-scale graph mining. He co-authored books Communication Networks: An Optimization, Control and Stochastic Networks Perspective (authors’ website), Cambridge University Press, 2014; and Diffusion Source Localization in Large Networks, Synthesis Lectures on Communication Networks, Morgan & Claypool Publishers, 2018.
He won the Young Investigator Award from the Defense Threat Reduction Agency (DTRA) in 2009 and the NSF CAREER Award in 2010. He was the Northrop Grumman Assistant Professor in the Department of Electrical and Computer Engineering at Iowa State University from 2010 to 2012. His papers have received the best paper award at IEEE INFOCOM 2015, the Kenneth C. Sevcik Outstanding Student Paper Award at ACM SIGMETRICS/IFIP Performance 2016, and the WiOpt’18 Best Student Paper Award; his papers have also been selected in ACM TKDD Special Issue “Best Papers of KDD 2016”, Fast-Track Review for TNSE at IEEE INFOCOM 2018 (7 out of 312 accepted papers were invited), and Best Paper Finalist at MobiHoc 2019.
Here is his Google Scholar Profile.
He is currently working on an introductory book on reinforcement learning. The draft is available here.