Presentations

Invited Presentations

  1. AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers. Technology and Artificial Intelligence Learning Seminar (TAILS), Montana State University. December 2026 (forthcoming).
  2. Bayesian Propensity Score Predictive Inference for Extending Trial Findings to Target Populations. SILVER Lab Meeting, Department of Epidemiology and Public Health, University of Maryland School of Medicine. August 2026.
  3. Nonparametric Bayesian Additive Regression Trees for Prediction and Missing Data Imputation in Longitudinal Studies. ENAR 2023 Spring Meeting, Nashville, TN, USA. Invited session: Bayesian Machine Learning for Decision-Making with Incomplete Information. March 2023.

Contributed Talks

  1. Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Data: Application to an Environmental Health Survey. JSM 2026, Boston, MA, USA. August 2026.
  2. AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers. STAI-X 2026, Boston, MA, USA. August 2026.
  3. Generalizing Treatment Effects from Trials to EHR Populations Using Propensity Score Predictive Inference. ENAR 2026 Spring Meeting, Indianapolis, IN, USA. March 2026.

Posters

  1. Jungang Zou, Alex Ziyu Jiang, and Qixuan Chen. AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers. STAI-X 2026, Boston, MA, USA. August 2026.
  2. Jungang Zou, Joseph E. Schwartz, Roderick Little, Nathalie Moise, and Qixuan Chen. Transporting Treatment Effects from Randomized Trials to EHR Populations Using Bayesian Propensity Score Predictive Inference. IMSI Workshop: New Horizons on Model Transportability and Data Integration, Chicago, IL, USA. June 2026.
  3. Jungang Zou and Liangyuan Hu. 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.
  4. Jungang Zou, Joseph E. Schwartz, Roderick Little, Nathalie Moise, and Qixuan Chen. Generalizing Treatment Effects from EHR-Recruited Trials Using Bayesian Propensity Prediction. 2025 Columbia Biostatistics Annual Research Symposium, New York, NY, USA. April 2025.
  5. Jungang Zou, Sijian Wang, and Qixuan Chen. Variable Selection for Multiply-Imputed Data: A Bayesian Framework. 2023 Columbia Biostatistics Annual Research Symposium, New York, NY, USA. September 2023.