Jungang Zou 🚀

Jungang Zou

(he/him)

Ph.D. student

Department of Biostatistics, Columbia University

Professional Summary

I am a fourth-year Ph.D. student in Biostatistics at Columbia University, advised by Dr. Qixuan Chen and Dr. Liangyuan Hu. In 2022, I received M.S. in Biostatistics at Columbia University. Before coming to Columbia, I earned my Bachelor’s degree in Computer Software Engineering at Xiamen University in China, advised by Dr. Fan Lin.

My research focuses on the development and application of Bayesian methods, particularly in the areas of missing data, causal inference, and survey analysis. I am also interested in advancing computational tools for efficient Bayesian analysis, with the goal of making these methods more practical and scalable for applied research in biostatistics.

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Education

PhD in Biostatistics

Columbia University

MS in Biostatistics

Columbia University

BE in Computer Software Engineer

Xiamen University

Interests

Bayesian Methods Missing Data Causal Inference Survey Analysis Statistical Computing
publications
Zidu Xu, Danielle Scharp, Mollie Hobensack, Jiancheng Ye, Jungang Zou, Sirui Ding, Jingjing Shang, Maxim Topaz (2024). Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review. Journal of the American Medical Informatics Association,, 21(1), 241-252.
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Sharifa Z. Williams, Jungang Zou, Yutao Liu, Yajuan Si, Sandro Galea, Qixuan Chen (2024). Improving Survey Inference Using Administrative Records Without Releasing Individual-Level Continuous Data. Statistics in Medicine, 43(30), 5803-5813.
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Abigail R. Greenleaf, Sarah Francis, Jungang Zou, Shannon M. Farley, T{\v{s}}epang Lekhela, Fred Asiimwe, Qixuan Chen (2024). Influenza-Like Illness in Lesotho From July 2020 to July 2021: Population-Based Participatory Surveillance Results. JMIR Public Health Surveill, 10, e55208.
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Chinelo Onyilofor, Baoyi Feng, Jungang Zou, Jennifer Mizhquiri Barbecho, Andrea T. Duran, Siqin Ye, Othanya Garcia, Jessica Singer, Qixuan Chen, Nathalie Moise (2024). Assessing the Fidelity of Depression Screening Implementation in Coronary Heart Disease Patients: A Cross‐Sectional Study. Journal of the American Heart Association, 13(21), e035550.
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Nina M. Flores, Stephanie Lovinsky-Desir, Adnan Divjan, Hoepner Lori A., Jungang Zou, Rachel L. Miller, Julie B. Herbstman, Frederica P. Perera, Matthew S. Perzanowski, Qixuan Chen (2024). Trajectory analysis of rhinitis in a birth cohort from lower-income New York City neighborhoods. Journal of Allergy and Clinical Immunology, 154(1), 111-119.
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preprints
Jungang Zou, Joseph E. Schwartz, Nathalie Moise, Roderick Little, Qixuan Chen (2025). Generalizing Treatment Effects from Trials to EHR Populations using Propensity Score Predictive Inference. Under preparation.
Keming Zhang, Yaoyao Li, Jungang Zou, Sijian Wang, Bernadette Fausto, Liangyuan Hu (2025). Multi-level variable selection using a BART-enhanced mixed-effects framework. Submitted.
Jungang Zou, Liangyuan Hu (2025). Nonparametric Bayesian Additive Regression Trees for Prediction and Missing Data Imputation in Longitudinal Studies. Under preparation.
Jungang Zou, Sijian Wang, Qixuan Chen (2025). Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Data.
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Kain Kim, Baoyi Feng, Mengxiao Luan, Jungang Zou, Amy Jones, Danielle Gadbois, Joseph E. Schwartz, Qixuan Chen, Nathalie Moise (2025). Evaluating sustained reach and effectiveness of collaborative care models: A Cross-sectional study of the New York State Collaborative Care Medicaid Program. Submitted.
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software
  • SBMTrees — Sequential Imputation with Bayesian Trees Mixed-Effects Models for Longitudinal Data CRAN • GitHub
  • AuxSurvey — Survey Analysis with Auxiliary Discretized Variables CRAN • GitHub
  • SAMTx — Sensitivity Assessment to Unmeasured Confounding with Multiple Treatments CRAN
  • BMIselect — Bayesian MI-LASSO Models for Variable Selection on Multiply-Imputed Data CRAN • GitHub
  • TMOGA — A Multi-Objective Genetic Algorithm for Dynamic Community Detection Problem PyPI • GitHub
presentations
  • Bayesian Machine Learning for Decision-Making with Incomplete Information
    ENAR 2023 Spring Meeting — Nashville, TN, USA — March 2023
posters
  • Generalizing Treatment Effect from EHR-Recruited Trials Using Bayesian Propensity Prediction
    Columbia Biostatistics Annual Research Symposium — New York, NY, USA — September 2025
  • Nonparametric Bayesian Additive Regression Trees for Prediction and Missing Data Imputation in Longitudinal Studies
    14th International Conference on Bayesian Nonparametrics — Los Angeles, CA, USA — June 2025
  • Variable Selection for Multiply-Imputed Data: A Bayesian Framework
    Columbia Biostatistics Annual Research Symposium — New York, NY, USA — September 2023