Research & Publications

Methodological Interests

My work bridges causal inference, Bayesian hierarchical modeling, and privacy-preserving federated learning, particularly focusing on how to handle realistic incomplete data and longitudinal EHR data across multi-institutional cohorts.

Working Papers & Preprints

  • Shen, Y., Kim, J., Luo, C., Zeger, S. L., Shah, A. A., Tong, J. (2026). MV-PEAL: A Federated Learning Framework for Multivariate Longitudinal EHR Data. [Submitted for the Annals of Applied Statistics]
    • Winner of the 2026 ICSA Student Paper Award
  • Shen, Y., Kim, J., Luo, C., Zeger, S., Domsic, R. Shah, A., Tong, J. (2026). Unlocking Multi-Institutional Insights into Disease Progression with Federated Learning: PEAL as a Lossless, One-Shot Solution. [In press at npj Digital Medicine]
    • 2026 AI Research Day Student Award
  • Vazquez, J., Shen, Y., Sanderson, K., Akulian, J., Tong, J., Stuart, E. A.(2026). Federated Learning with Incomplete Data: A Weighted Approach. [Submitted for Biostatistics]
  • Wu, X., Shen, Y., Shan, M., Stuart, E., Lipkovich, I. (2026). Comparing Federated Learning Methods for Estimating Average Treatment Effects in a Target Population from Multiple Real-world Studies and Randomized Trials. [Manuscript in preparation for Statistics in Medicine]
  • Chao, A., Shen, Y., Ghanta, A., Silver, N., Milardo, R., Santos, C., Tong, J. (2025). Sex Differences in Response to Incretin-Based Medications for Obesity: Systematic Review and Meta-Analysis. [Invited Revision at Obesity Reviews]
  • Shen, Y., Chu, H., Hong, H. (2025). Simulation-Based Methods for Power Calculation in Bayesian Network Meta-Analysis. [Invited revision at Journal of the Royal Statistical Society Series C]
    • Honorable Mention for the BEST Award for Master’s Research (2024)

Publications

  • Shen, Y., Bail, C., & Volfovsky, A. (2026). Enhancing joint ideal point estimation strategies with Twitter social networks and text data. Network Science, 14, e10. doi: 10.1017/nws.2026.10028
  • Shen, Y. (2022). Be Steady and Popular: a Modern Counter-Insurgency ABM. NetLogo Modeling Commons.
  • Shen, Y. (2022). Justified Cause? Assessing the Humanitarian Outcomes of US Foreign Aid and Intervention Since the Cold War. PoliS: Carleton Journal of Political Science, inaugural edition, pp.129-167.
    • Distinction on Senior Thesis - Political Science (2022)
  • Shen, Y., Flignor, J., Nachreiner, L., & Wang, K. (2022). Behind the Smoke: An Extreme Value Analysis of Air Pollution in Minnesota. Consortium for the Advancement of Undergraduate Statistics Education, spring 2022 issue.
    • First Prize in Undergraduate Statistics Research Project Competition (2022)
    • Distinction on Senior Thesis - Statistics (2022)

Book Chapters

  • Knoke, D. (2025). Insurging. In Network Collective Action: Agent-Based Models of Pandemics, Riots, Social Movements, Insurrections and Insurgencies (pp. 89-100). Cham: Springer Nature Switzerland. (Coauthored Chapter)

Invited Conferences & Presentations

2026

  • Joint Statistical Meeting (JSM)
  • ICSA Applied Statistics Symposium (Recipient of the NSF Travel Award)
  • Johns Hopkins inHealth Precision Medicine Symposium
  • PHAISE AI Research Day
  • Duke Industry Statistics Symposium (DISS)
  • Eastern North American Region (ENAR) Spring Meeting

2024

  • Eastern North American Region (ENAR) Spring Meeting
  • Duke Industry Statistics Symposium (DISS)
  • Duke Research Data Visualization Competition and Showcase

2023

  • New Directions in Analyzing Text as Data (TADA) Conference (Recipient of the TADA Travel Award)
  • Duke Health Data Science Poster Showcase

2021 – 2022

  • Electronic Undergraduate Statistics Research Conference (eUSR) (2022)
  • Northfield Undergraduate Mathematics Symposium (NUMS) (2021)
  • Carleton Undergraduate Research and Internship Symposium (2021)

Published Software

  • PDA: Privacy-Preserving Distributed Algorithms (2025). R Package. Co-developed with Luo, C., Duan, R., Tong, J., & Chen, Y. Available on CRAN
  • Model of Wheeler (2022). NetLogo Modeling Commons. Northwestern University Center for Connected Learning and Computer-Based Modeling, Evanston. Available Here