My resume can be found here [Resume].
🎓 I am a final-year Ph.D. candidate at Michigan State University supervised by Dr. Jiliang Tang. I am actively seeking industry position starting around May 2025. My research interests include Large Language Model, Recommender System, Information Retrieval, and Graph Machine Learning. If you know of any relevant openings, I would greatly appreciate your consideration! More Details can be found in [my research blog]
My academic research focuses on
- Network Analysis [paper1][paper2] and Graph Pre-training [paper1][paper2][Research Statement][Talk Slides]
- Enhance LLM with Better In-context Learning Ability [paper1][paper2][paper3]
Industrial Resource-efficient Solutions During Internships
- LLM-based Generative Recommendation (ongoing), Snap Research, User Modeling and Personalization Team
- LLM-based Ranking Algorithms [paper1][paper2], Baidu, Search Strategy Team
- Accelerate and Stabilize Neural Network Training [paper1][paper2], Microsoft Research Asia, Data Knowledge Intelligence Group
Transform Industrial Problems into Academic Challenges
- Organize Baidu WSDM CUP'23: Pre-training for Web Search.
- Organize Amazon KDD CUP'23: Multilingual Shopping Session Recommendation.
Moreover, I was engaged in academic-industry collaborations between MSU and several companies, including Graph Mining team in Google Research, Query Understanding team in Amazon, Intel Labs, J.P. Morgan AI Research. I led the graph research subgroup in my PhD lab, where I made my best memory collaborating closely with my talented labmates sharing the same goal. I am now serving as the organizer of the Learning on Graph Conference 2024, an exciting new conference facilitating graph and geometry community engagement.