Robotics engineer specializing in safety-critical autonomy for real-world robotic systems. At Toyota Research Institute of North America (TRINA), I build real-time planning and control systems for autonomous maneuvering of articulated vehicles, combining model-based optimization (MPPI/MPC) with diffusion-inspired trajectory sampling.

Previously, I developed SIL/HIL simulation pipelines for ADAS validation at Nikola Corporation, and built real-time adaptive safety controllers for physical human-robot interaction at Honda Research Institute.

My research on neural network repair — where learned control policies are formally corrected to satisfy safety constraints via mixed-integer optimization — has been published at CoRL, ICRA, IROS, and received a Best Workshop Paper Award at NeurIPS 2022. I have also contributed to risk-bounded control using stochastic barrier functions, behavior-aware motion planning for collaborative robots, and the Open X-Embodiment large-scale robot learning dataset.

Ph.D. in Computer Science from Arizona State University (co-advised by Heni Ben Amor and Georgios Fainekos), M.Sc. in Electrical Engineering from North Carolina A&T State University, and B.Sc. from Ferdowsi University of Mashhad. Full CV is available here.