Prof. Nidhi Seethapathi

Professor Seethapathi builds predictive models to help understand human movement with a combination of theory, computational modeling, and experiments. Her research focuses on understanding the objectives that govern movement decisions, the strategies used to execute movement, and how new movements are learned. By studying movement in real-world contexts using creative approaches, Seethapathi aims to make discoveries and develop tools that could improve neuromotor rehabilitation.

Research topics include:
(*) Understanding the objectives governing movement decisions -- We aim to study the computational objectives that govern movement decisions, the contexts in which they arise, and how different objectives are traded-off with one another. For instance, we have studied the role of energy, stability, and time in governing movement.

(*) Understanding the strategies used to execute movement -- We aim to study the internal and external variables that guide our actions, the mathematical relationship between these variables, and the algorithms by which they are coordinated. For instance, we have studied the internal variables that guide step to step locomotor control in the presence of noisy actuation.

(*) Understanding how new movements are learned -- We aim to study how new movements are selected in the face of novel demands, how the space of solutions is explored, and the ways in which learning can be improved. For instance, we have developed a theory of locomotor adaptation that predicts multiple observed experimental phenomena.