Forward and Inverse Problems in Combating Fake News πŸ—“ πŸ—Ί

University of Michigan 1005 EECS Building Map


Lei YingΒ Professor
University of Michigan, Department of Electrical Engineering and Computer Science


1005 EECS BuildingMAP


The proliferation of fake news on online social networks has eroded the public trust in news media and has become an imminent threat to the ecosystem of online social platforms like Facebook, Twitter, and Sina Weibo. This talk will review some forward and inverse problems in combating fake news, and will discuss two fundamental questions: (i) how to locate the source of fake news with partial observations? and (ii) how to quickly detect fake news at its early stage before it becomes viral?


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, and an Associate Editor of the IEEE Transactions on Information Theory. His research is broadly in the interplay of complex stochastic systems and big-data, including large-scale communication/computing systems for big-data processing, private data marketplaces, and large-scale graph mining. He coauthored books Communication Networks: An Optimization, Control and Stochastic Networks Perspective, Cambridge University Press, 2014; and Diffusion Source Localization in Large Networks, Synthesis Lectures on Communication Networks, Morgan & Claypool Publishers, 2018.