Robotics & Applied ML Engineer
Graduate research and projects in autonomous navigation, computer vision, SLAM, motion planning, and robot control.
01 · UC San Diego graduate research
At UC San Diego's Existential Robotics Laboratory, I built custom MuJoCo and dm_control environments for Ackermann-drive navigation with PPO and SAC, including obstacle generation, collision logic, and reward design.
02 · State estimation / Mapping
Fused stereo observations and IMU measurements with an extended Kalman filter to estimate motion and build a landmark map.
03 · ECE 228 team project
An ECE 228 team project for the Comma.ai Calibration Challenge, combining optical flow, vanishing-point geometry, and a Conv-LSTM model to estimate camera pitch and yaw from monocular driving video.
Based in India · Open to remote startup teams · View all projects
Background
Based in India · Open to remote startup teams
My path began with mechanical engineering and hands-on robotic systems, then moved through estimation and perception into learning-based decision-making. Graduate research at UC San Diego's Existential Robotics Laboratory focused on reinforcement learning for autonomous navigation under Prof. Nikolay Atanasov.
My work combines software with physical-system constraints such as sensor noise, vehicle dynamics, collision risk, and compute limits.
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