The Sharma research group focuses on integrating first principles and domain-specific knowledge with machine learning/AI techniques for design, analysis, and control of complex and large-scale dynamical systems, with an emphasis on digital twins. The objective is to develop scientific machine learning techniques that can learn physically interpretable and robust dynamic models with improved training efficiency and generalizability while simultaneously ensuring the exact satisfaction of physical laws. Drawing on tools and concepts from computational science, dynamics and control, and machine learning, the group develops principled data-driven methods for diverse applications ranging from soft robotics and structural dynamics to astrodynamics and computational physics.
Before joining the University of Wisconsin–Madison, Dr. Sharma was a Postdoctoral Research Scholar in the Department of Mechanical and Aerospace Engineering at the University of California, San Diego. He completed his PhD in Aerospace Engineering and his MS in Mathematics at Virginia Tech. He received his dual degree (BS + MS) in Mechanical Engineering from the Indian Institute of Technology–Bombay.