Saurabh Vyas

motor learning, dynamical systems, computational neuroscience

Saurabh Vyas is a Bioengineering PhD student at Stanford where he studies neural mechanisms underlying motor learning by using a combination of electrophysiology in awake and behaving animals, brain-machine interfaces, and dynamical systems theory. He received B.S. degrees in Biomedical Engineering and Electrical Engineering, and an M.S.E. in Biomedical Engineering all from Johns Hopkins, where he studied neural dynamics in patients with Parkinson’s disease and epilepsy using statistical control theory. After Hopkins, Saurabh was a research engineer at the Applied Physics Laboratory where he worked on several projects involving computer vision, medical imaging, and robotics. At Stanford, Saurabh has been a co-instructor for courses on neural engineering, and biomedical data analysis, as well as a teaching assistant for courses on machine learning, and biomechanics. He also co-founded the Computational Neuroscience Journal Club. After Stanford, Saurabh will be a postdoc at MIT, studying how neural dynamics in prefrontal and other cognitive areas support motor planning and closed-loop control.