Praveen Venkatesh

Praveen Venkatesh (Member, IEEE) received the B.Tech. degree (Hons.) in electrical engineering from the Indian Institute of Technology, Madras, India, in 2014, and the M.S. and Ph.D. degrees in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, PA, USA, in 2017 and 2021, respectively. He is currently a Scientist and a Shanahan Foundation Fellow at the Allen Institute, Seattle, WA, USA. Over the last few years, he has developed new measures of information flow in the brain, studied fundamental limits and algorithms for EEG source localization, and conducted experimental design and data analysis with EEG and ECoG data. Recently, he has worked on understanding partial information decompositions and on applying information measures to the field of fairness in machine learning. His research interests lie broadly at the intersection of information theory, signal processing, neuroscience, and neuroengineering. Dr. Praveen was a recipient of Henry L. Hillman Presidential Fellowship, the Dowd Fellowship from the College of Engineering, and the CMLH Fellowship in Digital Health from the Center for Machine Learning and Health, all at Carnegie Mellon University. He was the inaugural recipient of the Shanahan Foundation Fellowship at the Interface of Data and Neuroscience, co-hosted by the Allen Institute and the University of Washington, Seattle. He has served as a Lecturer for the tutorial on information theory for neural inference at the 2021 IEEE International Symposium for Information Theory.