Information Theory, Probability and Statistical Learning: A Festschrift in Honor of Andrew Barron (Hardcover) (ISBN-13: 9783032139917)

Ioannis Kontoyiannis is with the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge, where he is the Churchill Professor of Mathematics of Information. He has been awarded the Manning endowed assistant professorship; a Sloan Foundation Research Fellowship; an honorary Master of Arts Degree Ad Eundem by Brown University; and a Marie Curie Fellowship. He is a Fellow of the IEEE, the IMS, the AAIA, and the AIAA. He has published over 60 journal articles in leading international journals and over 120 conference papers in the top international conferences. He also holds two U.S. patents, and he has authored a textbook in probability theory. He has served on the editorial board of the American Mathematical Society's Quarterly of Applied Mathematics, the IEEE Transactions on Information Theory, Springer-Verlag's Acta Applicandae Mathematicae, the book series Lecture Notes in Mathematics by Springer-Verlag, and the online journal Entropy.

Jason M. Klusowski is an Assistant Professor in the Department of Operations Research and Financial Engineering (ORFE) at Princeton University. Prior to joining Princeton, he was an Assistant Professor in the Department of Statistics at Rutgers University-New Brunswick. He received a Ph.D. in Statistics and Data Science from Yale University. His research explores the tradeoffs among interpretability, statistical accuracy, and computational feasibility in large-scale, data-driven systems. He is a recipient of the Alfred P. Sloan Research Fellowship in Mathematics, the National Science Foundation (NSF) CAREER Award, and the Howard B. Wentz, Jr., Junior Faculty Award from Princeton's School of Engineering and Applied Science (SEAS). He currently serves as an Associate Editor for the probability and statistics journal Bernoulli.

Cynthia Rush is an Associate Professor of Statistics at Columbia University. She received a Ph.D. and M.A. in Statistics from Yale University in 2016 and 2011, respectively, and she completed her undergraduate coursework at the University of North Carolina at Chapel Hill where she obtained a B.S. in Mathematics in 2010. Her research focuses on high-dimensional statistics, message passing algorithms, statistical robustness, and information theory. Cynthia currently serves as an Associate Editor for Bernoulli and the IEEE Transactions on Information Theory.