Hi, I'm Arnav. I recently finished my MS in Mechatronics and Robotics, and I spend most of my time building robots that can perceive, plan, and learn. My background covers computer vision, reinforcement learning, and autonomous localization.
I like problems where code has to deal with the messiness of the real world. That usually means writing perception pipelines that hold up under real conditions, or training agents that make decisions in real time.
New York University — New York, NY
MS GPA 3.75 · BS GPA 3.7 · Dean's List 2021–2024.
Coursework: Reinforcement Learning, Robot Locomotion, Computer Vision, Control Systems, Mechatronics, FEA.
NYU Dept. of Mechanical and Aerospace Engineering
Ran lab sessions and provided technical guidance to undergrads. Handled grading for assignments and quizzes.
HCL Technologies
Built an end-to-end perception pipeline with OpenCV and YOLOv8 to detect safety equipment in QSR environments. Trained detection models under varied lighting and occlusion conditions, reaching a baseline mAP50 of 52%.
InnovFusion Tech
Ran FEA on structural components to check stress, fatigue, and deformation. Design iterations from simulation data increased component lifecycle by 126% and cut peak stress by 22%.
A selection of robotics and software engineering projects. Full source on GitHub.