Data Driven Learning and Control seminar series is organized by the Information and Decision Science Lab at Cornell University and aims to explore the latest advancements and interdisciplinary approaches to data-driven learning and control systems.
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Bio: Ilya Kolmanovsky earned his Ph.D. in aerospace engineering (flight dynamics and control) from the University of Michigan in 1995, alongside an M.A. in mathematics completed the same year. He also holds an M.S. in aerospace engineering from Michigan (1993). His doctoral research focused on motion planning and feedback control for nonholonomic dynamic systems, with applications to attitude control of underactuated multibody spacecraft.
Kolmanovsky joined the University of Michigan’s Department of Aerospace Engineering in January 2010 where he has been appointed as a full professor (with tenure) since September 2013 and as a Pierre T. Kabamba Collegiate Professor of Aerospace Engineering since September 2023.
His current research aims at advancing control theory for systems with state and control constraints, including Model Predictive Control and Reference Governors. He also focuses on the modeling, dynamics, and control for advanced spacecraft, aircraft, automotive vehicles and engines and propulsion systems.
Before returning to the academia, Kolmanovsky spent nearly 15 years at Ford Research and Advanced Engineering in Dearborn, MI, progressing from postdoctoral researcher to technical leader in powertrain control. His work at Ford centered on control of advanced internal combustion engines and powertrain systems to improve transient response and drivability, increase fuel and energy efficiency, and reduce emissions.