Summary
Tianyu Shi is a researcher and Ph.D. engineer with 8+ years bridging cutting-edge reinforcement learning, multi-agent systems, and LLM agent research with real-world AI productization. Trained at University of Toronto, McGill, UC Berkeley and MILA, he has authored 40+ publications across top venues (ICML, NeurIPS, ACL, ICRA, Nature sub-journals) and accumulated 800+ citations with an H-index of 21. He has a track record of industrial collaboration and system deployment with companies like Momenta, Megvii, and startups such as Skywork AI, complementing academic supervision and teaching experience. Tianyu maintains long-standing research partnerships with top labs (Tsinghua, Peking, MIT, DeepMind, Meta) and blends project incubation skills with large-scale AI system expertise. Notably, his background spans both transportation engineering and foundational AI, enabling cross-disciplinary solutions from autonomous driving to agent orchestration.
7 years of coding experience
2 years of employment as a software developer
Visiting student researcher, Visiting student researcher at University of California, Berkeley
Doctor of Philosophy - PhD Engineering, Doctor of Philosophy - PhD Engineering at University of Toronto
Bachelor's degree vehicle engineering, Bachelor's degree vehicle engineering at Beijing Institute of Technology
Master of Engineering - MEng(thesis) Major in Transportation Engineering minor in Computer Science, Master of Engineering - MEng(thesis) Major in Transportation Engineering minor in Computer Science at McGill University
English, German, Chinese