Seminar

Everywhere we turn these days, we find that networks are appropriate descriptions of underlying interactions. In the tech world, we see the Internet, the World Wide Web, mobile phone networks, and a variety of online social networks. In economics, we are increasingly experiencing both the positive and negative effects of a networked economy. In epidemiology, we find disease spreading over our ever growing social networks, complicated by mutation of the disease agents. In biomedical research, we are beginning to understand the structure of gene regulatory networks, with the prospect of using this understanding to manage many human diseases. In this talk, I look quite generally at some of the models to describe these networks, processes on the networks, algorithms on the networks, and finally, methods to infer network structure from measured data. I'll discuss in detail particular applications to (1) recommendation systems, using machine learning to infer recommendations from sparse data sets on bipartite networks; and (2) cancer genomics, applying network algorithms to identify possible drug targets.



Bio:

Jennifer Tour Chayes is Technical Fellow, Managing Director and co-founder of three Microsoft Research labs in New England, New York City and Montreal. Before joining Microsoft, Chayes was Professor of Mathematics at UCLA. She is the author of about 150 academic papers and inventor of about 30 patents. Her research includes phase transitions in discrete math and computer science, structural and dynamical properties of networks, graph theory, graph algorithms, algorithmic game theory, computational biology, machine learning, and responsible AI. Chayes is co-inventor of the field of graphons, which are widely used for estimation and machine learning of networks at scale.



Chayes holds a B.A. in biology and physics from Wesleyan, where she graduated first in her class, and a Ph.D. in mathematical physics from Princeton. She did postdoctoral work in the Mathematics and Physics Departments at Harvard and Cornell. She is the recipient of the NSF Postdoctoral Fellowship, the Sloan Fellowship, the UCLA Distinguished Teaching Award, and the Anita Borg Women of Vision Leadership Award, among many other leadership awards. She has twice been a member of the Institute for Advanced Study in Princeton. Chayes is a Fellow of the American Association for the Advancement of Science, the Fields Institute, the Association for Computing Machinery, and the American Mathematical Society. She is a Member of the American Academy of Arts and Sciences, and the National Academy of Sciences. Chayes holds an Honorary Doctorate from Leiden University. She is winner of the 2015 John von Neumann Award, the highest honor of the Society for Industrial and Applied Mathematics.