1. SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning (pre-print, under review)
2. SUQL: Conversational Search over Structured and Unstructured Data with Large Language Models (Findings of NAACL 2024)
3. SPINACH: SPARQL-Based Information Navigation for Challenging Real-World Questions (Findings of EMNLP 2024)
4. Fine-tuned LLMs Know More, Hallucinate Less with Few-Shot Sequence-to-Sequence Semantic Parsing over Wikidata (EMNLP 2023)
5. Coding Reliable LLM-based Integrated Task and Knowledge Agents with GenieWorksheets (Proceedings of ACL 2025)
Research Experience
1. AI research intern at Meta during summer 2025, working with Kai Sun, Scott Yih, and Luna Dong on RL for knowledge extraction.
Education
1. Ph.D in Computer Science, Stanford University, 2022 - 2026 (Expected), Advisor: Prof. Monica S. Lam
2. B.S. (w. Honors) in Computer Science & in Mathematics, Minor in Physics, The University of Chicago, 2022
3. Quarter-long exchange, California Institute of Technology, Autumn 2021
Background
Fourth-year CS Ph.D. at Stanford focusing on real-life, practical NLP problems, often drawing perspectives from computer systems and programming languages. Recent research focuses on knowledge agents with LLMs, aiming to enable domain-independent approaches that effectively retrieve and navigate different sources of knowledge, including structured, unstructured, and hybrid data.