From Shannon to Machine Learning 4/23/19
319 DeBartolo Hall
Dr. Erik Stauffer
Abstract:
Communication Theory and Machine Learning have shared parallel histories. Beginning with the early pioneering days, both share a common foundation in information processing. As time has unfolded, advancements in each of these areas reveal vital connections between them. Given recent exciting developments, it is increasingly likely that each of these fields will have profound impacts on the other in the future.
Biography:
Erik Stauffer received his B.S. degree in electrical engineering from the University of Illinois, Urbana-Champaign, in 2001 and M.S. and Ph.D. degrees in electrical engineering from Stanford University, in 2003 and 2006. Following his time spent in the Smart Antenna Research Group with Prof. Arogyaswami Paulraj, he was then recruited by Beceem Communications in 2006 and subsequently joined Broadcom in 2010. Since 2014 Erik has been with Google in Mountain View, California. He has multiple IEEE journal publications, conference papers, and numerous patents. Erik’s research interests include wireless communication, information theory, multiple-input multiple-output (MIMO) systems, coding, optimization, and machine learning.