Rate My Professor Maurice Smith

Maurice Smith is the Gordon McKay Professor of Bioengineering in the Harvard John A. Paulson School of Engineering and Applied Sciences, where he also holds appointments in the Center for Brain Science. He earned a bachelor’s degree in biomedical engineering, electrical engineering, and mathematics from Vanderbilt University in 1993. In 2003, he received an M.D./Ph.D. in biomedical engineering from the Johns Hopkins University School of Medicine, winning the David Israel Macht Prize for graduate student basic science research. Smith completed a two-year postdoctoral fellowship in the Department of Biomedical Engineering at Johns Hopkins before joining Harvard as an assistant professor in 2005. He was promoted to associate professor and then to full professor with tenure in 2015. Smith directs the Harvard Neuromotor Control Lab, focusing on the neural mechanisms of motor control and learning through experimental paradigms involving human subjects, robotics, and computational modeling grounded in control theory.

Smith’s research spans computational neuroscience, biomechanics, motor control, and the application of stochastic systems and robotics. His seminal contributions include highly cited works such as “Error correction, sensory prediction, and adaptation in motor control” (Annual Review of Neuroscience, 2010), “Interacting adaptive processes with different timescales underlie short-term motor learning” (PLoS Biology, 2006), “Temporal structure of motor variability is dynamically regulated and predicts motor learning ability” (Nature Neuroscience, 2014), and “The role of variability in motor learning” (Annual Review of Neuroscience, 2017). He received the Alfred P. Sloan Research Fellowship and the McKnight Scholar Award in 2007. In 2020, Smith was elected to the College of Fellows of the American Institute for Medical and Biological Engineering for pioneering advances in understanding the neural basis of motor function using mathematical principles from control theory. He teaches courses such as Physiological Systems Analysis (BE 110) and has delivered seminars on motor behavior and learning.