Liam Tan
Mathematics PhD student at the University of Illinois Chicago.
I am a mathematics PhD student at the University of Illinois, Chicago. I previously did my undergrad at UC Berkeley, where I double majored in Mathematics and Computer Science. Prior to doing math, I dabbled in AI/RL research and was advised by Sergey Levine.
Research interests
- Mathematical Logic. Ideas in computability theory, model theory, and set theory.
Other Interests
- AI in Math. Closely following progress in mathematical abilities of autonomous AI agents such as GPT 5.6 Sol and Claude Fable. Interested in autoformalization and autonomous proof agents.
- Scaling and Self-Improvement in AI. Interested in the AI stack: pretraining, scaling, parallelism, post-training and RL, harnesses and safety, distillation and quantization, and agentic swarms.
- Stats/TCS/EE. Vaguely interested in applied math related to probability, optimization, and theoretical computer science.
Teaching
| Term | Course | Subject | Role |
|---|---|---|---|
| Spring 2022 | CS 70 | Discrete Mathematics and Probability Theory | Reader |
| Fall 2022 | CS 170 | Algorithms | Reader |
| Spring 2023 | CS 182 | Deep Learning | Tutor |
| Spring 2023 | EECS 126 | Probability and Random Processes | Reader |
| Fall 2023 | CS 182 | Deep Learning | Tutor |
| Spring 2024 | Student Learning Center | Upper-division mathematics | Tutor |
| Fall 2026 | TBD | TBD | TBD |
Publications
Mathematics
Characterizing relative decidability in terms of model completeness
Matthew Harrison-Trainor, Liam Tan
Under review, 2026
AI & Robotics
Multi-Stage Cable Routing through Hierarchical Imitation Learning
Jianlan Luo*, Charles Xu*, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine
IEEE Transactions on Robotics (TRO), 2024
FMB: A Functional Manipulation Benchmark for Generalizable Robotic Learning
Jianlan Luo*, Charles Xu*, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine
International Journal of Robotics Research (IJRR), 2024
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration
IEEE International Conference on Robotics and Automation (ICRA), 2024
* Equal contribution.
Last updated August 2026.