Paper 'A Pre-training Framework for Relational Data with Information-theoretic Principles' accepted to NeurIPS 2025; 'TopoX: A Suite of Python Packages for Machine Learning on Topological Domains' published in the Journal of Machine Learning Research (JMLR); 'Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes' accepted to AAAI 2024; received the NeurIPS 2025 Scholar Award.
Research Experience
Worked on various projects including computer vision, specifically vehicle re-identification and 3D object detection. Currently focusing on graph-related machine learning and topological deep learning.
Education
Ph.D. student at Michigan State University, supervised by Dr. Jiliang Tang; M.S. from Dartmouth College; B.S. in Computer Science, summa cum laude, from Texas Christian University.
Background
A second-year Ph.D. student at Michigan State University, supervised by Dr. Jiliang Tang. Before joining MSU, he earned his M.S. from Dartmouth College and graduated summa cum laude in Computer Science from Texas Christian University. His research interests broadly include graph-related problems, machine learning on graphs, and topological deep learning. He has previously worked on computer vision projects, specifically vehicle re-identification and 3D object detection.
Miscellany
Open to collaborations and discussions. Feel free to reach out via email.