Huimin Cheng, PhD

Huimin Cheng is an Assistant Professor in the Department of Biostatistics at Boston University.  She received a PhD in statistics from the University of Georgia in 2023 and a master’s degree at the Central University of Finance and Economics.

Cheng works closely with biophysicists, engineers, computer scientists, political scientists, public health scientists,  and sociologists to solve scientific problems arising from various disciplines. Her methodological research focuses on statistical network analysis, graph deep learning, causal inference, machine learning, and Riemannian geometry. Cheng modeled the generating process of a network from both non-parametric (e.g., graphon model) and parametric (e.g., SBM) perspectives. She has developed various methods, including network cross-validation, network sampling, network ANOVA, and graphon convolutional network. 

Research interests include Bioinformatics, Causal Inference, Econometrics, Nonparameteric Regression, Statistical Network Analysis, Riemanian Geometry.