Jeff Moehlis

Jeff Moehlis is a Professor in the Department of Mechanical Engineering at the University of California, Santa Barbara (UCSB), affiliated with the College of Engineering. His research focuses on control theory, dynamical systems, and their applications to neuroscience and biomedical engineering. He explores topics such as neural oscillator synchronization, optimal control strategies for biological systems, and nonlinear dynamics in energy harvesting systems.

Moehlis's work integrates mathematical modeling with computational methods, addressing challenges in phase reduction techniques, stochastic systems, and collective behavior in populations. His contributions span theoretical advancements (e.g., Hamilton-Jacobi equation solutions) and practical applications (e.g., deep brain stimulation optimization and robotic control systems). He maintains an active research group and collaborates across disciplines to advance understanding of complex systems.

His publications emphasize interdisciplinary approaches, leveraging machine learning, symbolic regression, and data-driven methods to analyze and control systems ranging from neural networks to energy harvesting devices. Moehlis's office is located in ENGR II RM. 2350, and he can be reached via moehlis@engineering.ucsb.edu.