About Me
I am a 5th 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.
During my PhD, I have also had the fortune to collaborate with and receive advice from Tobias Gerstenberg and Tatsunori Hashimoto.
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.
I’m constantly working on new projects and seeking to connect with people! Drop me an email if you want to talk about research or academic/industry life!
Contact me
Teaching
(assistant)
- 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 Reviewer
- ICLR 2022, 2023 Reviewer
- NeurIPS 2021, 2022, 2023 Reviewer