Gautam Dasarathy (Electrical and Computer Engineering, Rice University)

Gautam Dasarathy is a Postdoctoral Fellow in the Electrical and Computer Engineering department at Rice University where he is hosted by Rich Baraniuk. Before this, he spent time in the Machine Learning Department at Carnegie Mellon University where he worked with Aarti Singh. He received his Ph.D. in Electrical Engineering from the University of Wisconsin - Madison, where he was advised by Dr. Robert Nowak and Dr. Stark Draper. His research interests include topics in Machine Learning, Signal Processing, Statistics, and Information Theory. In particular, he is interested in understanding how to model, learn, and leverage interactions in large complex systems.

Mladen Kolar (University of Chicago Booth School of Business).

Mladen Kolar is Assistant Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His research is focused on high-dimensional statistical methods, graphical models, varying-coefficient models and data mining, driven by the need to uncover interesting and scientifically meaningful structures from observational data. Particular applications arise in studies of dynamic regulatory networks and social media analysis. Mladen was a co-organiser of the NIPS 2012, NIPS 2013, NIPS 2014 and NIPS 2016 workshops on Modern Nonparametric Methods in Machine Learning.

Richard Baraniuk (Electrical and Computer Engineering, Rice University)

Richard Baraniuk is the Victor E. Cameron Professor of Electrical and Computer Engineering at Rice University and Founding Director of Connexions (cnx.org) and OpenStax (openstax.org). His research interests lie in the areas of signal, image, and information processing and include machine learning and compressive sensing. He is a member of the American Academy of Arts and Sciences and a fellow of the National Academy of Inventors, American Association for the Advancement of Science, and IEEE. He has received the DOD Vannevar Bush Faculty Fellow Award (National Security Science and Engineering Faculty Fellow), the IEEE Signal Processing Society Technical Achievement Award, and the IEEE James H. Mulligan, Jr. Education Medal. He holds 28 US and 4 foreign patents that have been licensed to a large multinational corporation and a startup. He has co-organized multiple NIPS workshops on machine learning for education.