Hello there 👋.
I’m a robotics software engineer at Aurora Innovation, developing self-driving tech.
I’m interested in developing intelligent robot systems capable of contextual reasoning and action. I’d like to deploy these robots onto the noisy real world, where the robots can (1) infer underlying structures about the problem and the world, (2) synthesise feasible plan sequences exploiting the structure and prior experiences, and (3) execute them robustly, handling failures.
I graduated from UC San Diego with a master’s degree in Computer Science and Engineering at the University of California, San Diego, specializing in robotics. Here, I conducted my research at the Cognitive Robotics Lab at the Contextual Robotics Institute, UCSD, where I worked on developing a task planning improvisational framework for robot tool use through causal affordances. (Thesis). I also worked on Experience based Task and Motion Planning for manipulation tasks, the most recent of which was presented at RSS 2024.
When I’m not doing robotics, you’d typically find me watching cricket or football (re: soccer) or passionately defending why the Eagles could not have carried the ring to Mordor.
Download my (semi-up-to-date) CV
MS in Computer Science & Engineering, 2023
University of California, San Diego
BE in Computer Science & Engineering, 2020
RV College of Engineering
(2024). Motion Planning in Foliated Manifolds using Repetition Roadmap. Robotics Science and Systems (RSS). |
(2023). Household navigation and manipulation for everyday object rearrangement tasks. International Conference on Robotic Computing (IRC). |
(2023). Deep-Feature-Based Visual Odometry for Autonomous Emergency Parking. Proceedings of the 2023 6th International Conference on Advances in Robotics. |
(2019). Adaptive real time traffic prediction using deep neural networks. IAES International Journal of Artificial Intelligence. |
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