Dept. of Mechanical Engineering Graduate Seminar

PRESENTATION: Advances in data-driven and learning-based methodologies have enabled unprecedented autonomy in many engineered systems, but intelligent modeling and control of fluid flows have yet to be realized. Motivated by the enormous potential of intelligent interactions between engineered systems and fluid flows across many applications, my research seeks to bridge the gap between data-driven, computational, and experimental fluid mechanics. This talk will explore three research thrusts demonstrating the potential of flow-informed systems and technologies in the real world.

PRESENTER: Dr. Peter I. Renn is a staff scientist at the California Institute of Technology, where he conducts research at the intersection of artificial intelligence and experimental fluid mechanics. He earned his PhD in Aeronautics from Caltech in 2023 under the mentorship of Professor Morteza Gharib, receiving the William F. Ballhaus Prize for an outstanding doctoral dissertation. Dr. Renn's work focuses on data-driven modeling and intelligent control of fluid flows in real-world engineered systems. Prior to his current role, he served as a quantitative strategist at Virtu Financial, where he developed high-frequency algorithmic trading strategies and furthered his expertise in real-time data-informed decision making. Dr. Renn's work has been supported by organizations such as the National Science Foundation, RTX, Verizon, and the Technology Innovation Institute.