Engineered a rapidly deployable autonomous ground robot capable of exploring, mapping, and navigating previously unseen terrain. Developed an interpretable autonomy stack, implemented online mapping and real-time replanning, and developed a Python data access layer over ROS2 bag files. Deployed full autonomy stack on embedded onboard compute.

Proposed a sampling-based weight-space projection framework for enforcing safety constraints during policy updates. Formulated policy optimization as a convex projection and derived sufficient stability conditions. Empirically demonstrated safe performance gains in regression and imitation learning.

Reviewed three submissions for IFAC World Congress 2026, one submission for IEEE CASE 2025, and one IEEE RA-L journal submission.

Designed a constraint-aware imitation learning framework incorporating an actor-critic structure. Improved training efficiency by 150% and reduced collision rates by 60% in CARLA simulation. Integrated reachability-based safety filters. Oral presentation at IEEE IROS 2025.

Led a team of four undergraduate students on vision-based off-road vehicle dynamics modeling and path planning.

Developed a vehicle dynamics simulator based on dynamic bicycle model with gymnasium APIs. Implemented a CARLA connector.

Led discussions and office hours. Developed labs and exams on Python, MATLAB, and numerical methods.

Developed a CNN-based end-to-end controller for high-speed autonomous racing using RGB camera input. Trained using imitation learning and deployed on a 1:10 Jetson-powered vehicle. Achieved long rollouts without constraint violation.