Published several papers, including 'Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies', 'SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations', and more, with presentations at ICLR, NeurIPS, and other significant conferences.
Research Experience
Currently an Applied Scientist at Amazon Search. Serves as Area Chairs at multiple conferences including Language and Molecule @ ACL, Scaling Environments for Agents @ NeurIPS, and serves in the program committees of several other conferences.
Education
Ph.D. in Computer Science from Texas A&M University, advised by Prof. Shuiwang Ji; B.S. in Statistics from the School of the Gifted Young at the University of Science and Technology of China.
Background
An Applied Scientist at Amazon Search. Research interests include Large Language Models, Retrieval Augmented Generation, Multi-Modality, Self-Supervised Learning and Foundation Models, Model Explanability, Graph Neural Networks, and AI4Science (Geometric Deep Learning, Bioinformatics, Biomedical Imaging).