V John Mathews
Professor, Electrical and Computer Engineering
Oregon State University

This talk will be divided into two parts. The first part will involve some signal processing/control theory-based perspectives on stochastic gradient learning. In particular, we will discuss a lowpass-regularized framework for accelerated learning that contains many momentum-based learning algorithms as special cases. We will discuss how a control systems perspective may be employed to derive parameter update algorithms and characterize their learning behavior. The second part of this talk will describe efforts to interpret human motor intent from bioelectrical signals. The estimated movement intent may be used to intuitively control (i.e., control by thought) prosthetic limbs. We will present a semi-supervised online learning algorithm for movement intent estimation and share experimental results demonstrating the ability of this approach to tackle time-varying characteristics of the neuro-musculoskeletal system.

V John Mathews is a professor in the School of Electrical Engineering and Computer Science at the Oregon State University. He received his Ph.D. and M.S. degrees in electrical and computer engineering from the University of Iowa, Iowa City, Iowa in 1984 and 1981, respectively, and the B.E. (Hons.) degree in electronics and communication engineering from the Regional Engineering College (now National Institute of Technology), Tiruchirappalli, India in 1980. Prior to 2015, he was with the Department of Electrical & Computer Engineering at the University of Utah. He served as the chairman of the ECE department at Utah from 1999 to 2003, and as the head of the School of Electrical Engineering and Computer Science at Oregon State from 2015 to 2017. His current research interests are in nonlinear and adaptive signal processing and application of signal processing and machine learning techniques in neural engineering, biomedicine, and structural health management. Mathews is a Fellow of IEEE. He has held many leadership positions of the IEEE Signal Processing Society. He is a recipient of the 2008-09 Distinguished Alumni Award from the National Institute of Technology, Tiruchirappalli, India, IEEE Utah Section’s Engineer of the Year Award in 2010, and the Utah Engineers Council’s Engineer of the Year Award in 2011. He was a distinguished lecturer of the IEEE Signal Processing Society for 2013 and 2014, and is the recipient of the 2014 IEEE Signal Processing Society Meritorious Service Award.

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