About

Path Robotics

Staff Engineer and Tech Lead for Obsidian 2.0, Path Robotics' latest AI stack powering autonomous welding. Leading a team of ML, Software, and Robotics Engineers, researching and deploying state of the art motion planning algorithms for ambidextrous industrial robots. Holder of 3 US patents in robotic tool calibration, path clearance planning, and simulated weld path generation. Applying reinforcement learning and machine learning to push the boundaries of fully autonomous robotic systems — from research to production.

Carnegie Mellon University

Masters in Mechanical Engineering and Robotics (Research) with a 4.0/4.0 GPA. Supervised by Dr. Maxim Likhachev and Dr. Kenji Shimada. Researcher at the Search Based Planning Laboratory. Coursework in Reinforcement Learning, Motion Planning, Computer Vision, SLAM, Adaptive Control, Self-Driving Cars, and Machine Learning.

Delhi Technological University

Bachelors in Mechanical Engineering (2014–2018).

Certifications

Focus Areas