Yao Li, Ph.D.

Yao Li received the B.S. degree in electrical engineering from Sichuan University, Chengdu, China in 2002 and Ph.D. degree in electrical and computer engineering from the University of Maryland, College Park in 2010. Since then, he has been working as a research associate at the department of biomedical engineering, University of Southern California. He is mainly interested in the application of control theory and modeling of complex systems to the understanding and treatment of human sensorimotor disorders. He was a visiting scholar at the National Center for Simulation in Rehabilitation Research (NCSRR) at Stanford University in 2011. He has developed a nonlinear optimal control model to provide insights into stability of sway in standing humans, a common research paradigm used to characterize various disorders of balance and senility.  He has been developing a sparse optimal estimation algorithm (SOME) for deriving command signals from the residual peripheral nervous system of amputees. This algorithm combined with the advanced electrode technology for chronic recording from ventral root axons will great enhance the quality of the command signals available to control sophisticated prosthetic limbs with many actuated joints. He is also closely involved in the development and experimental validation of models of sensorimotor learning that have important clinical implications and robotic applications of a robust tactile sensor array that mimics the mechanical properties and distributed touch receptors of the human fingertip. He is a member of IEEE, Society of Neuroscience, Society for the Neural Control of Movement, and American Society of Biomechanics.