San Francisco Bay Area
Robotics engineer with broad experience from computer vision and perception through planning and control. Inspired to solve meaningful and challenging real-world problems using state-of-the-art technology! Eager to work hard and learn continuously.
Anything and everything required to get self-driving 4-wheeled robots widely.
Leading the autonomy software team for the Tesla Autopilot. My team's main focus areas are: - Creation of large scale automatic ground truth pipelines to train neural networks with massive amounts of diverse, high-quality data. Use this fleet-learning approach to replace potentially brittle run-time algorithms with robust learned models. - Developing an accurate and detailed geometric and semantic understanding of the world using the best of both machine-learned and engineered models. - Building robust, causal, predictive models for other agents in both geometry and semantic state spaces. - Decision making, motion planning, and control modules using state-of-the-art AI techniques including methods for high-dimensional search, trajectory optimization, reinforcement learning, model-predictive control, etc.
Worked on geometric scene understanding to significantly improve the performance of Autopilot using fleet learning techniques.
Research and development of a robust, camera-based, perception system to recognize and register various road-marks on the vehicle's drivable road surface in-order to precisely localize the car. This project was part of the autonomous driving team of Volkswagen.
Vehicle Dynamics and Control * Worked on brake actuation modules to establish real-time performance guarantees of actuators * Development and validation of onboard and offboard diagnostics software for vehicle's Electronic Control Unit * Development and testing of embedded software for interfacing and controlling actuation devices