Huimin Cheng

Huimin Cheng, PhD

Assistant Professor, Biostatistics - Boston University School of Public Health


My research is highly interdisciplinary. My methodological research focuses on statistical network analysis, graph deep learning, causal inference, machine learning, and Riemannian geometry. I modeled the generating process of a network from both non-parametric (e.g., graphon model) and parametric (e.g., SBM) perspectives. I have developed various methods, including network cross-validation, network sampling, network ANOVA, and graphon convolutional network.

I also work closely with biophysicists, engineers, computer scientists, political scientists, public health scientists, and sociologists to solve scientific problems arising from various disciplines. (1) Single-molecule and nanotechnology research. We analyzed single-molecule force spectroscopy data to reveal the binding modes in intermolecular analysis. The proposed method paves a revolutionary path to the massive production and fully automated system for precise intermolecular analysis, such as the interaction between transcription factors and DNA. (2) Political science research. We analyzed how the transnational advocacy network simultaneously provides social power and exacerbates global inequalities. (3) Smart grid research. We applied network methods to detect and localize anomalies in smart grids. (4) Public health and Bioinformatics research. I developed various methods to promote data analytics in gastric cancer, obstructive sleep apnea, and coronary heart disease. Recently, I have been particularly interested in developing methods for spatial transcriptomics, including spatial domain segmentation. (5) Smart cities research. We analyzed transportation networks to promote the smart city.


  • University of Georgia, PhD Field of Study: Statistics
  • Central University of Finance and Economics, MS Field of Study: Statistics
  • Hubei University of Economics, BS Field of Study: Statistics


  • Published on 1/1/2024

    Wang, Z., Cheng, H. M., Zhong, W. X., Ma, P., and Murdie, A. . Shifting Sands: How Change-Point and Community Detection Can Enrich our Understanding of International Politics. Accepted by International Interactions. 2024.

  • Published on 8/14/2023

    He Y, Martinez L, Ge Y, Feng Y, Chen Y, Tan J, Westbrook A, Li C, Cheng W, Ling F, Cheng H, Wu S, Zhong W, Handel A, Huang H, Sun J, Shen Y. Social Mixing and Network Characteristics of COVID-19 Patients Before and After Widespread Interventions: A Population-based Study. Epidemiol Infect. 2023 Aug 14; 151:1-38. PMID: 37577939.

    Read At: PubMed
  • Published on 1/1/2023

    Wu, S. S., Cheng, H. M., Cai, J. Z., Ma, P., and Zhong, W. X. Subsampling for Large Graphs Using Ricci Curvature. International Conference on Learning Representations (ICLR). 2023.

  • Published on 1/1/2022

    Yu, J., Cheng, H. M., Zhang, J. N., Zhong, W. X., Ye, J., Song, W. Z., and Ma, P. CONGO$^2$: Colored-node Graph Square Model for Anomaly Detection and Localization in Smart Grids. IEEE Internet of Things Journal. 2022.

  • Published on 8/23/2021

    Cheng H, Yu J, Wang Z, Ma P, Guo C, Wang B, Zhong W, Xu B. Details of Single-Molecule Force Spectroscopy Data Decoded by a Network-Based Automatic Clustering Algorithm. J Phys Chem B. 2021 Sep 02; 125(34):9660-9667. PMID: 34425052.

    Read At: PubMed
  • Published on 6/11/2021

    Zhang J, Zhu H, Chen Y, Yang C, Cheng H, Li Y, Zhong W, Wang F. Ensemble machine learning approach for screening of coronary heart disease based on echocardiography and risk factors. BMC Med Inform Decis Mak. 2021 Jun 11; 21(1):187. PMID: 34116660.

    Read At: PubMed
  • Published on 3/25/2021

    Wang Y, Meagher RB, Ambati S, Cheng H, Ma P, Phillips BG. Patients with Obstructive Sleep Apnea Have Altered Levels of Four Cytokines Associated with Cardiovascular and Kidney Disease, but Near Normal Levels with Airways Therapy. Nat Sci Sleep. 2021; 13:457-466. PMID: 33790678.

    Read At: PubMed
  • Published on 1/1/2021

    Cheng, H. M., Wang, Y., Ma, P., and Murdie, A. Communities and Brokers: How the Transnational Advocacy Network Simultaneously Provides Social Power and Exacerbates Global Inequalities. International Studies Quarterly. 2021.

  • Published on 11/12/2020

    Huang LC, Yeung W, Wang Y, Cheng H, Venkat A, Li S, Ma P, Rasheed K, Kannan N. Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction. BMC Bioinformatics. 2020 Nov 12; 21(1):520. PMID: 33183223.

    Read At: PubMed
  • Published on 1/1/2020

    Wang HS, Cheng HM. Renmin University of China Press. Business Data Analytics and Its Applications With R. 2020.

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