About Me
I am a final year CS PhD student at Stanford University. I am a part of Stanford Artificial Intelligence Laboratory (SAIL).
- PhD in Computer Science: Reinforcement Learning, Education. Advised by Emma Brunskill, Chris Piech.
- MS in Symbolic Systems: specialized in Information Theory, Coding Theory, Statistical Signal Processing. Advised by Noah Goodman, Dan Jurafsky, James Zou.
In 2019, I rotated with Chris Piech (Fall 19’), Chris Potts (Winter 20’), and Emma Brunskill (Spring 20’). Currently, I am co-advised by Emma Brunskill and Chris Piech, focusing on developing algorithms that supports human decision making.
In 2023, Microsoft Research (MSR) Summer Internship, mentored by Adith Swaminathan and Ching-An Cheng on LLM RL Agent. Our work results in an open-source library Trace.
During my PhD, I have also had the fortune to collaborate with and receive advice from Tobias Gerstenberg, Tatsunori Hashimoto, and Noah Goodman.
I am interested in a wide range of topics in AI, but they generally fall into the following categories:
- Reinforcement Learning / Efficient Decision Making Systems for Social Good
- Causal inference and Causal Reasoning
- Language Understanding
- AI/Human Alignment through Statistics and Cognitive Science
As an effort to increase diversity in the field of AI/Tech, I mentor students from the underrepresented group.
Contact me
Teaching
(assistant)
- 2023 Spring: CS31N Counterfactuals: The Science of What Ifs?
- 2022 Winter: CS234 Reinforcement Learning
- 2018 Spring: CS224U Natural Language Understanding
- 2017 Spring: CS224S Spoken Language Processing
- 2016 Winter: CS224N Natural Language Processing
Community Service
- Program Committee, Foundation Models for Decision Making Workshop, NeurIPS 2022 Workshop, New Orleans
- Program Committee, Reinforcement Learning Ready for Production Workshop, AAAI 2023
- ICML 2022, 2024 Reviewer
- ICLR 2022, 2023 Reviewer
- NeurIPS 2021, 2022, 2023, 2024 Reviewer