2025: Invited talk at Berkeley Agentic AI Summit; Released new work 'Can Past Experience Accelerate LLM Reasoning?'; Talk on LLM Reasoning Efficiency at INFORMS 2025; Two first-author papers accepted by ACL 2025 Main and KDD 2025 ADS Track, one co-author paper accepted by KDD 2025 Benchmark Track.
2024: Paper 'Distilling Large Language Models for Text-Attributed Graph Learning' accepted by CIKM’24; Co-organizer for LLMs4Bio workshop at AAAI 2024!
Research Experience
PhD SWE Intern, Machine Learning at Meta (Summer 2025); AI for Science Research Intern at Merck (Summer 2024); Machine Learning Engineer Intern at DiDi (Jun 2021 - Dec 2021).
Education
Ph.D. in Computer Science from Emory University (2022 - Present); B.S. in Software Engineering from Tsinghua University (2018 - 2022).
Background
Research interests: Graph Machine Learning, LLM Reasoning, and AI for Science. Currently a third-year PhD student in the Department of Computer Science at Emory University, advised by Dr. Liang Zhao.