Jiayi (Jessie) Tong

I will be joining the Department of Biostatistics at Johns Hopkins University as an Assistant Professor in August 2024. I received my Ph.D. at the Department of Biostatistics, Epidemiology and Informatics at Perelman School of Medicine at the University of Pennsylvania, where I'm fortunate to be advised by Dr. Yong Chen. Previously, I received a B.S. with High Honors in Applied Mathematics from the University of California, San Diego in 2017.

My thesis committee is chaired by Dr. Rebecca A. Hubbard with members, Dr. David A. Asch, Dr. Christopher B. Forrest, Dr. Jason Moore, and Dr. Yong Chen.

Email  /  CV  /  Google Scholar  /  Twitter  /  Github

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With an overall theme of clinical evidence generation and evidence synthesis with real-world data (RWD), my research interests span:

  • Clinical evidence generation using data from distributed research networks
  • Surrogate-assisted semi-supervised learning
  • Systematic reviews and meta-analyses

I am also passionate about collaborative research in various fields, including opioid use disorder (OUD), dementia and other aging conditions, acute myocardial infarction, pediatric conditions, mental health disorder, long-COVID, hematology, vaccine effectiveness, health disparity and fairness, and health policy.

Selected Publications

    Clinical Evidence Generation Using Real-world Data

A new end-to-end data aggregation approach for comparing hospital performance without sharing patient-level data
Jiayi Tong, Jenna M. Reps, Chongliang Luo, Martijn J. Schuemie, Chao Yan, Patrick B. Ryan, Haitao Chu, Jiang Bian, Elizabeth A Shenkman, Yiwen Lu, Juan Manuel Ramirez-Anguita, Milou T. Brand, Zhaoyi Cheng, Scott L. DuVall, Thomas Falconer, Alex Mayer Fuentes, Kevin Hen, Jing Li, Michael E. Matheny, Miguel A. Mayer, Bhavnisha Patel, Di Wang, Ross D. Williams, Katherine Simone, Sarah Seager, James Yang, Yujia Zhou, Jeffrey S. Morris, Fei Wang, Elizabeth A. Stuart, Harlan M. Krumholz, Hua Xu, Rachel M. Werner, Marc A. Suchard, Thomas Lumley, Bradley A. Malin, David A. Asch, Yong Chen.
(2023 JSM Student Award)
Github page

Real-world Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents
Qiong Wu*, Jiayi Tong* (co-first author), Bingyu Zhang, Dazheng Zhang, Jie Xu, Yishan Shen, Lu Li, L. Charles Bailey, Jiang Bian, Dimitri A. Christakis, Megan L. Fitzgerald, Kathryn Hirabayashi, Ravi Jhaveri, Alka Khaitan, Tianchen Lyu, Suchitra Rao, Hanieh Razzaghi, Hayden T. Schwenk, Fei Wang, Margot I. Witvliet, Eric J. Tchetgen Tchetgen, Jeffrey S. Morris, Christopher B. Forrest, Yong Chen.
Accepted by The Annals of Internal Medicine

On the proportional likelihood ratio model for sparse data
Jiayi Tong, Annie Qu, Raymond J. Carroll, Yang Ning, Yong Chen.
Invited revision at The Annals of Applied Statistics, 2023

Evaluating Site-of-Care-Related Racial Disparities in Kidney Graft Failure Using a Novel Federated Learning Framework
Jiayi Tong, Yishan Shen, Alice Xu, Xing He, Chongliang Luo, Mackenzie Edmondson, Dazheng Zhang, Yiwen Lu, Chao Yan, Ruowang Li, Lianne Siegel, Lichao Sun, Elizabeth A Shenkman, Sally C. Morton, Bradley A. Malin, Jiang Bian, David A. Asch, Yong Chen.
Invited revision at Journal of the American Medical Informatics Association (JAMIA), 2023

Advancing Interpretable Regression Analysis for Binary Data: A Novel Distributed Algorithm Approach
Jiayi Tong, Lu Li, Jenna Marie Reps, Vitaly Lorman, Naimin Jing, Mackenzie Edmondson, Xiwei Lou, Ravi Jhaveri, Kelly J. Kelleher, Nathan M. Pajor, Christopher B. Forrest, Jiang Bian, Haitao Chu, Yong Chen.
Invited revision at Statistics in Medicine, 2023

DisC2o-HD: Distributed Causal inference with covariates shift for analyzing real-world high-dimensional data
Jiayi Tong* (co-first author), Jie Hu*, George Hripcsak, Yang Ning, Yong Chen.
Under review at the Journal of Machine Learning Research, 2023

Distributed learning for heterogeneous clinical data with application to integrating COVID-19 data across 230 sites
Jiayi Tong, Chongliang Luo, Md Nazmul Islam, Natalie E. Sheils, John Buresh, Mackenzie Edmondson, Peter A. Merkel, Ebbing Lautenbach, Rui Duan and Yong Chen
npj Digital Medicine, 2022
Paper / Github page

Robust-ODAL: Learning from heterogeneous health systems without sharing patient-level data
Jiayi Tong* (co-first author), Rui Duan*, Ruowang Li, Martijn J. Scheuemie, Jason H. Moore, Yong Chen
Pacific Symposium on Biocomputing (PSB) , 2020
Paper / Github page

    Surrogate-assisted semi-supervised learning

An augmented estimation procedure for EHR-based association studies accounting for differential misclassification
Jiayi Tong, Jing Huang, Jessica Chubak, Xuan Wang, Jason H Moore, Rebecca A Hubbard, Yong Chen
Journal of the American Medical Informatics Association (JAMIA) , 2019
Paper / Github page

A cost-effective chart review sampling design to account for phenotyping error in electronic health records (EHR) data
Ziayan Yin, Jiayi Tong, Yong Chen, Rebecca A Hubbard, Cheng-Yong Tang
Journal of the American Medical Informatics Association (JAMIA) , 2021

An Augmented Estimation Procedure for EHR-based Association Studies with Multiple Surrogate Outcomes
Yiwen Lu*, Jiayi Tong* (co-first author), Rebecca A Hubbard, Yong Chen
Under review at Journal of the American Medical Informatics Association (JAMIA) , 2023
Github page

    Systematic reviews and Meta-analyses

Confidence Score: A Data-Driven Measure for Inclusive Systematic Reviews Considering Unpublished Preprints
Jiayi Tong, Chongliang Luo, Yifei Sun, Rui Duan, M. Elle Saine, Lifeng Lin, Yifan Peng, Yiwen Lu, Anchita Batra, Anni Pan, Olivia Wang, Ruowang Li, Arielle Anglin, Yuchen Yang, Xu Zuo, Yulun Liu, Jiang Bian, Stephen E. Kimmel, Keith Hamilton, Adam Cuker, Rebecca A. Hubbard, Hua Xu, Yong Chen.
Invited revision at Journal of the American Medical Informatics Association (JAMIA)

Advancing timely and reliable evidence synthesis in the era of COVID-19: A novel method for including preprints in systematic reviews
Jiayi Tong, Yifei Sun, Rebecca A. Hubbard, M. Elle Saine, Hua Xu, Xu Zuo, Lifeng Lin, Chunhua Weng, Christopher Schmid, Stephen E. Kimmel, Craig A. Umscheid, Adam Cuker, Yong Chen
Under review at JAMA network open

Meta-analysis of Reference Ranges
Wei Liang*, Jiayi Tong* (co-first author), Haitao Chu, Nicolas Rodondi, Christine Baumgartner, Anne R. Cappola, Raymond J. Carroll, Yong Chen
Under review at Biometrics

    Scientific papers

Quantifying and correcting bias due to outcome dependent self-reported weights in longitudinal study of weight loss interventions
Jiayi Tong, Rui Duan, Ruowang Li, Chongliang Luo, Jason H. Moore, Jingsan Zhu, Gary D. Foster, Kevin G. Volpp, William S. Yancy, Jr., Pamela A. Shaw, Yong Chen.
Scientific Reports, 2023

Identifying Clinical Risk Factors for Opioid Use Disorder using a Distributed Algorithm to Combine Real-World Data from a Large Clinical Data Research Network
Jiayi Tong, Zhaoyi Chen, Rui Duan, Wei-Hsuan Lo-Ciganic, Tianchen Lyu, Cui Tao, Peter A. Merkel, Henry R. Kranzler, Jiang Bian, Yong Chen
American Medical Informatics Association (AMIA) Annual Symposium Proceedings, 2019
Paper / Github page

Practice Environmenn Scale of the Nursing Work Index: A Descriptive Statistics Meta-Analysis
Eileen T. Lake, Bingyu Zhang, Jiayi Tong, Gloria Mpundu, Kelsey N. Gross, Bingyu Zhang, Priscilla Cho, Yong Chen
Invited Revision at International Journal of Nursing Studies, 2023
Food insecurity and binge eating: A systematic review and meta‐analysis
Jessica A. Abene, Jiayi Tong, Jeffrey Minuk, Gretchen Lindenfeldar, Yong Chen, and Ariana M. Chao.
International Journal of Eating Disorders, 2023
Adding caplacizumab to standard of care in thrombotic thrombocytopenic purpura: a systematic review and meta-analysis
Mia Djulbegovic, Jiayi Tong, Alice Xu, Joanna Yang, Yong Chen, Adam Cuker, and Allyson M. Pishko
Blood Advances, 2023
Inherited thrombophilia and the risk of arterial ischemic stroke: a systematic review and meta‐analysis
Thita Chiasakul, Elizabeth De Jesus, Jiayi Tong, Yong Chen, Mark Crowther, David Garcia, Chatree Chai‐Adisaksopha, Steven R. MessĂ©, and Adam Cuker
Journal of the American Heart Association, 2019
The Use of Likelihood Ratio Test to Identify Rare Adverse Events with Year-varying Reporting Rates for FLU4 Vaccine in VAERS
Jiayi Tong, Jing Huang, Jingcheng Du, Yi Cai, Cui Tao, Yong Chen
American Medical Informatics Association (AMIA) Annual Symposium Proceedings, 2018


PDA: Privacy-preserving Distributed Algorithms
PDA-OTA: Privacy-preserving Distributed Algorithms Over The Air
Xmeta: A Comprehensive Toolbox for Meta-analysis


Teaching Assistant, "Clinical Evidence Generation using EHR data", JSM 2023
Teaching Assistant, "Practical Solutions for Working with EHR Data", JSM 2022
Session Chair, "Distributed Regressions in Real-World Data", JSM 2021
Session Chair, "Advanced Methods for Pharmacoepidemiology", ENAR 2021
Teaching Assistant, BSTA 754: Advanced Survival Analysis, Fall 2022
Teaching Assistant, BSTA 656: Longitudinal Data Analysis, Fall 2022
Teaching Assistant, BSTA 660: Design of Observational Studies, Fall 2021
Teaching Assistant, BSTA 661: Design Of Interventional Studies, Fall 2021
Teaching Assistant, "Regression Methods: Concepts and Applications", Summer Institute in Statistical Genetics (SISG) 2022