Huimin Cheng, PhD
Assistant Professor
Boston University School of Public Health

PhD, University of Georgia
MS, Central University of Finance and Economics
BS, Hubei University of Economics

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.

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

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  1. 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.
  2. 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.View Related Profiles. PMID: 37577939; PMCID: PMC10540215; DOI: 10.1017/S0950268823001292;
  3. 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.
  4. 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.
  5. 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; DOI: 10.1021/acs.jpcb.1c03552;
  6. 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; PMCID: PMC8196502; DOI: 10.1186/s12911-021-01535-5;
  7. 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; PMCID: PMC8006954; DOI: 10.2147/NSS.S282869;
  8. 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.
  9. 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; PMCID: PMC7664030; DOI: 10.1186/s12859-020-03842-6;
  10. Wang HS, Cheng HM. Renmin University of China Press. Business Data Analytics and Its Applications With R. 2020.
Showing 10 of 17 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 17 publications over 9 distinct years, with a maximum of 4 publications in 2019 and 2021


2022 Southeastern Conference: Emerging Scholars Award ($35,000)
2022 Georgia Statistics Day: 1st Place Student Poster Presentation Award
2022 University of Georgia: Summer Research Grant ($1,500)
2021 Department of Statistics, University of Georgia: Best Beginning student
2021 Oconee County School: Outstanding Mentor
2019 University of Georgia: Entrepreneurial Team Lead of UGA NSF I-Corps program
2019 University of Georgia: Bargmann Travel Fund for The 2019 Joint Statistical Meetings
2017 Central University of Finance and Economics: National Scholarship
2017 Central University of Finance and Economics: Excellent Graduate of Beijing
2017 Central University of Finance and Economics: Distinguished Graduation Thesis Award
Contact for Mentoring:

801 Massachusetts Ave
Boston MA 02118
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