Summary
Alvin Huang is a full-stack robotics software engineer with 10 years of experience building production-grade autonomy, motion planning, and embedded systems across startups and large tech firms. He has designed and shipped core navigation, SLAM, and motion controllers that achieved millimeter-level tracking and led to multiple patents while optimizing C++ systems for real-world robot deployment. Alvin co-founded and scaled an AI startup, managing a 20+ person technical team and delivering ML, NLP, and operational research solutions that dramatically improved client optimization runtimes. He’s worked on vehicle simulation and test-case generation for autonomy at Uber and now applies his low-level systems rigor to trading tech at Jane Street. Trained at University of Toronto and Carnegie Mellon, he combines academic depth with a pragmatic focus on performance, calibration pipelines, and deployable algorithms. Notably, he moves heavy computation to compile-time and designs deployment procedures that reduce map deformation and improve robustness in human-populated environments.
10 years of coding experience
7 years of employment as a software developer
Bachelor of Applied Science - BASc, Mechatronics, Robotics, and Automation Engineering, 3.91/4.00, Bachelor of Applied Science - BASc, Mechatronics, Robotics, and Automation Engineering, 3.91/4.00 at University of Toronto
Master of Science - MS, Mechatronics, Robotics, and Automation Engineering, 4.08, Master of Science - MS, Mechatronics, Robotics, and Automation Engineering, 4.08 at Carnegie Mellon University
English, Chinese