Research Interests

I’m interested in designing RL environments in which agents can genuinely learn. Designing a non-hackable environment is a lot like sculpting a work of art. As agents become more capable, the environments they require grow increasingly complex, and the distinction between a well-designed environment and a poorly designed one becomes ever more consequential. I am convinced that environments will become the most crucial component of post-training.

Previously, I worked on post-training LLMs for efficiency (reducing token and tool usage), safety (abstention), and general capability (math and question answering). Back then, I mainly designed rewards that shaped model behavior, along with tasks that probed how well those rewards worked.

Education

Cornell
Ph.D. in Computer Science
2023 – 2026
Stanford
Visiting Student in Computer Science
2025
UESTC
B.S. in Information and Computing Sciences
2018 – 2022

Experience

Meta
FAIR Alignment
Dec 2025 – May 2026
Adobe
Adobe Research
May 2025 – Aug 2025

📫 Contact

Email: jinyansu6[@]gmail.com