Scholar
Chi Jin
Google Scholar ID: GINhGvwAAAAJ
Assistant Professor, Princeton University
Machine Learning
Optimization
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Citations & Impact
All-time
Citations
11,770
H-index
47
i10-index
69
Publications
20
Co-authors
65
list available
Contact
Email
chij@princeton.edu
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Publications
26 items
LeAct: Learning to Reason from Expert Actions
2026
Cited
0
Goedel-Architect: Streamlining Formal Theorem Proving with Blueprint Generation and Refinement
2026
Cited
0
Agent Bazaar: Enabling Economic Alignment in Multi-Agent Marketplaces
2026
Cited
0
Continual Harness: Online Adaptation for Self-Improving Foundation Agents
2026
Cited
0
Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning
2026
Cited
0
Awakening the Sleeping Agent: Lean-Specific Agentic Data Reactivates General Tool Use in Goedel Prover
2026
Cited
0
Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification
2026
Cited
0
Automatic Generation of High-Performance RL Environments
2026
Cited
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Resume
Academic Achievements
Princeton AI Lab Seed Grant, 2025
Sloan Research Fellowship, 2024
NSF CAREER Award, Division of Information and Intelligent Systems, 2023
E. Lawrence Keyes, Jr./Emerson Electric Co. Faculty Advancement Award, 2023
Princeton Commendation for Outstanding Teaching (ECE524), 2022 & 2024
Princeton Commendation for Outstanding Teaching (ECE539), 2021 & 2023
Princeton SEAS Innovation Award, 2022
Best Paper Award, ICLR 2022 Workshop on Gamification and Multiagent Solutions
Best Paper Award, ICML 2018 Workshop on Exploration in Reinforcement Learning
Published Goedel-Prover (COLM 2025) and Goedel-Prover-V2 (arXiv), establishing the strongest open-source theorem prover to date
Research Experience
Assistant Professor (now Associate Professor) at Princeton University, Department of Electrical and Computer Engineering
Leads research on LLM reasoning & agents, game theory & MARL, statistical learning, and optimization
Teaches courses including ECE524 (Foundations of Reinforcement Learning), ECE539/COS512, and COS511/ECE434/COS434
Delivered a tutorial on multiagent reinforcement learning at the Simons Institute
Principal investigator of the Goedel-Prover project on automated theorem proving with LLMs
Background
Associate Professor of Electrical and Computer Engineering, Princeton University
Associated Faculty Member of Computer Science
Research focuses on decision-making aspects of machine learning
Develops intelligent agents capable of advanced reasoning, strategic planning, and complex task execution
Contributions span theoretical foundations of reinforcement learning, multi-agent learning, game theory, statistical learning theory, and optimization
Currently extending work to AI for mathematics and games, with emphasis on grounded and verifiable AI systems
Co-authors
18 total
Michael I. Jordan
Professor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley
Praneeth Netrapalli
Google DeepMind
Qinghua Liu
OpenAI
Sham M Kakade
Harvard University
Tiancheng Yu
Two Sigma
Yu Bai
OpenAI
Zhaoran Wang
Associate Professor at Northwestern University
Zhuoran Yang
Yale University