Hello, and welcome to my webpage!
I recently completed my PhD in control systems at the Department of Applied Mathematics working at the Hybrid Systems Lab supervised by Prof. Jun Liu. I completed my undergraduate and master's degrees in electrical engineering at K. N. Toosi University of Technology, where I was a member of the APAC research group.
I am passionate about solving real-world problems through machine learning, data-driven optimization, and control. My research introduces a theoretical framework for designing reliable and efficient safety-critical control methods by integrating the formal guarantees of classical control with the adaptability of machine learning techniques. My thesis title is "Learning-Based Safety-Critical Control Under Uncertainty with Applications to Mobile Robots".The key areas of my work include:
Trajectory tracking with provably safe performance: Developing a novel framework that systematically enforces multiple safety constraints to a tracking controller based on MPC.
Learning-based robust safety-critical controllers: Developing a data-driven approach based on GP to learn the impact of model uncertainty on high-order safety certificates and incorporating the uncertainty-aware high-order safety constraint with an arbitrary robust controller.
Path planning for tractor-trailer systems: Designing provably safe autonomous parking path planning methods for truck-trailers (parallel and perpendicular).
For more details about my background, please visit my LinkedIn page.
