Ph.D. Student in Computer Science, University of Virginia
guanghui [AT] virginia.edu
My name is Guanghui Min (pronunciation: /ɡwɑːŋ-hweɪ mɪn/), a second-year Computer Science Ph.D. student at University of Virginia. I am very fortunate to be advised by Prof. Chen Chen.
My current interests focus on Graph Machine Learning and Theory as well as their applications in Epidemiology, Chemistry, Financial Markets and so on.
I completed my Master's degree in Applied Statistics at the University of Michigan, Ann Arbor in 2020, supervised by Prof. Kerby Shedden. Prior to that, I earned my Bachelor's degree in Statistics from the School of Mathematics and Statistics at Wuhan University. I worked as a full-time Senior Machine Learning Engineer at the Innovation Center of Yinhua Fund Management Co., Ltd, a leading public fund (with an AUM exceeding 1 trillion CNY, as of 2021) in mainland China from 2020 to 2024.
‡ indicates equal contribution. Full publications on Google Scholar.
Scaling Epidemic Inference on Contact Networks: Theory and Algorithms
Guanghui Min, Yinhan He, Chen Chen
NeurIPS'25: The 39th Annual Conference on Neural Information Processing Systems. 2025.
Exploring Generative Approaches for Predicting Copolymer Sequences from Reaction Conditions
Guanghui Min‡, Wenxin Xu‡, Kateri DuBay, Chen Chen
NeurIPS'25 AI for Science Workshop. 2025.
Scaling Epidemic Inference on Contact Networks: Theory and Algorithms
Guanghui Min, Yinhan He, Chen Chen
NeurIPS'25: The 39th Annual Conference on Neural Information Processing Systems. 2025.
Demystifying Epidemic Containment in Directed Networks: Theory and Algorithms
Yinhan He, Chen Chen, Song Wang, Guanghui Min, Jundong Li
WSDM'25: The 18th ACM International Conference on Web Search and Data Mining. 2025.
Full Resume in PDF. (Updated on Oct 27, 2025)
This website uses the website design and template by Prof. Martin Saveski.