Sina Heydari, Santa Clara University
Abstract: Biological organisms exhibit remarkable proficiency in locomotion. From sea stars walking on rocky and uneven terrains to microscopic organisms swimming through
viscous fluids, they are well-adapted to their environments. Effective motion in such environments requires the ability to sense local cues, infer information about their surroundings, and use that information for effective navigation and control. This challenge becomes particularly pronounced in complex fluid environments, such as vortical flows, where swimmers must adapt dynamically to unpredictable conditions, or in Stokes flow where viscous forces are dominant and inhibit swimming. In this talk, I will explore how recent advances in artificial intelligence (AI) can be applied to the design of bio-inspired swimmers operating in various environments. I will specifically focus on three model problems: a three-link fish in potential flow, a pair of schooling swimmers, and a microswimmer navigating a low-Reynolds number environment. In each case, I will show how AI-powered control enables these agents to overcome the inherent difficulties of locomotion in their respective environments. Together, these results highlight the transformative potential of AI in enabling adaptive and robust locomotion in fluid environments.
Bio: Dr. Sina Heydari is currently a Research Associate and Lecturer at Santa Clara University and an incoming Assistant Professor in the Department of Mechanical Engineering at California State University, Northridge. He earned a Ph.D. in Mechanical Engineering from the University of Southern California in 2023. He also holds an M.S. in Mechanical Engineering from the University of Southern California and a B.S. in Mechanical Engineering from Sharif University of Technology. His research focuses on locomotion of biological systems, with an emphasis on fluid-structure interactions and their applications to complex biological systems, such as schools of fish. An emerging area of his work integrates physics-based models with Artificial Intelligence algorithms to control and optimize bioinspired engineering systems. Dr. Heydari’s research has been featured in prominent media outlets, including the BBC and KQED.
Meeting ID: 949 8137 6707
Passcode: 325164