Published multiple papers in several international conferences such as RecSys'25, ICWSM'25, ECML PKDD'24, etc. Research areas covered non-parametric graph convolution for re-ranking in recommendation systems, scaled supervision as an implicit Lipschitz regularizer, how to improve representation alignment and uniformity in graph-based collaborative filtering, and more.
Research Experience
Interned as a data scientist intern at Microsoft AI during summer 2024 and 2025; Interned as an applied scientist intern at Amazon AWS in New York City in fall 2025.
Education
Ph.D. student in Computer Science at Dartmouth College, advised by Prof. Soroush Vosoughi.
Background
Research interests broadly lie in cognitive modeling in artificial intelligence (e.g., agentic memory, preference modeling), recommender systems (e.g., graph-based collaborative filtering, click-through-rate prediction) and graph representation learning over various domains (e.g., healthcare, mobile application promotion). Born and raised in Jiangxi, China.