Jin Jin

Jin_08_23.jpeg

Department of Biostatistics, Epidemiology and Bioinformatics
University of Pennsylvania, Perelman School of Medicine
203 Blockley Hall, 423 Guardian Drive
Philadelphia, PA 19104

I am an Assistant Professor of Biostatistics at the University of Pennsylvania, Department of Biostatistics, Epidemiology and Informatics. I worked as a postdoctoral fellow in Dr. Nilanjan Chatterjee’s group at the Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health in 2019 - 2023. I received my Ph.D. in Biostatistics from the University of Minnesota, Twin Cities under the supervision of Drs. Joeseph S. Koopmeiners and Lin Zhang. Before that I received my Bachelor’s degree in statistics from the School of the Gifted Young, University of Science and Technology of China (USTC).

My research interests focus on developing statistical and computational methods to address cutting-edge problems in public health and medicine by integrating large-scale, multi-source datasets. Within this scope, my research involves health equity in disease risk prediction, statistical genetics, Bayesian hierarchical models for high-dimensional, complex-structured data, and statistical data integration.

In September 2025, I received an NIH Maximizing Investigators’ Research Award (MIRA) from the National Institute of General Medicine Sciences (NIGMS) on Statistical methods and tools for enhancing polygenic risk prediction and discovery of causal gene pathways.
 

Contact

Department of Biostatistics, Epidemiology and Bioinformatics
University of Pennsylvania, Perelman School of Medicine
3600 Civic Center Blvd, 3E-307
Philadelphia, PA 19104
Email: Jin.Jin@Pennmedicine.upenn.edu

 

news

Mar 03, 2026 Our preprint on Constructing a Literature-Derived Database for Benchmarking Polygenic Risk Score Construction Methods with Ranking Inferences is now available on medRxiv.
Sep 30, 2025 Dr. Jin received a Maximizing Investigators’ Research Award (MIRA) from the National Institute of General Medicine Sciences (NIGMS) on Statistical methods and tools for enhancing polygenic risk prediction and discovery of causal gene pathways.
Sep 30, 2025 Our paper on Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage) was published in the Journal of the American Statistical Association.
Jan 25, 2025 PennPRS version 1.0.0 is now available online. Preprint
Sep 04, 2024 Dr. Jin was awarded a three-year Innovation Award to establish the Penn Center for Eye-Brain Health (PennEBH) from the Center for Clinical Epidemiology and Biostatistics (CCEB) at Penn Medicine.
Apr 10, 2024 Our paper on MUSSEL, a method for developing enhanced ancestry-specific polygenic risk score, is now available on Cell Genomics.
Mar 15, 2024 Our paper on MRLE: Mendelian randomization analysis using multiple biomarkers of an underlying common exposure, was published in Biostatistics.

publications

2025

  1. PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine
    Jin Jin, Bingxuan Li, Xiyao Wang, and 8 more authors
    medRxiv, 2025

2024

  1. MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups
    Jin Jin, Jianan Zhan, Jingning Zhang, and 8 more authors
    Cell Genomics, 2024
  2. Mendelian randomization analysis using multiple biomarkers of an underlying common exposure
    Jin Jin, Guanghao Qi, Zhi Yu, and 1 more author
    Biostatistics, 2024

2022

  1. T2-DAG: a powerful test for differentially expressed gene pathways via graph-informed structural equation modeling
    Jin Jin and Yue Wang
    Bioinformatics, 2022

2021

  1. Individual and community-level risk for COVID-19 mortality in the United States
    Jin Jin, Neha Agarwala, Prosenjit Kundu, and 4 more authors
    Nature Medicine, 2021