Jiebiao Wang

Jiebiao Wang

Associate Professor of Biostatistics (Primary) and Clinical and Translational Science (Secondary), University of Pittsburgh

Jiebiao Wang, PhD

I'm an Associate Professor in the Department of Biostatistics and Health Data Science (Primary) and the Clinical and Translational Science Institute (Secondary) at the University of Pittsburgh. Before Pitt, I was a postdoc at Carnegie Mellon with Dr. Kathryn Roeder, and earned my PhD in Biostatistics from the University of Chicago with Drs. Lin Chen and Robert Gibbons.

My lab develops statistical and computational methods for high-dimensional genomic data, with a focus on single-cell and spatial omics, cellular deconvolution, and causal mediation analysis. We collaborate broadly on the biology of complex diseases — Alzheimer's disease, psychiatric disorders, asthma, and cancer — using whole-genome sequencing, bulk and single-cell RNA-seq, DNA methylation, and proteomics.

Current funding: R01AG080590 · Statistical methods for population-level cell-type-specific analyses of tissue omics data for Alzheimer's disease; and R21AG087057 · Heterogeneous genetic effects and mediation in Alzheimer's disease.

Research themes

Theme 01

Single-cell & spatial omics

Statistical methods that turn population-scale single-cell and spatial transcriptomic, epigenomic, and proteomic data into cell-type-specific biological insight.

Theme 02

Cellular deconvolution

A family of methods — MIND, bMIND, EnsDeconv, HiDecon, scMD, BLEND, EMixed — that estimate cell-type composition and cell-type-specific expression from bulk tissue.

Theme 03

Causal mediation

Genomic mediation analysis and heterogeneous causal methods (HMBART) for dissecting how genetic variation propagates through molecular intermediates to disease.

Featured methods

HMBART mediation diagram with BART trees
Mediation2026

HMBART

Heterogeneous causal mediation analysis with Bayesian additive regression trees.

Liu C, Qin X, Talisa VB, Wang J. Biometrics, accepted.

code

BLEND posterior integration of single-cell references
Deconvolution2025

BLEND

Probabilistic cellular deconvolution with individualized single-cell reference integration.

Huang P, Cai M, McKennan C, Wang J. Genome Biology, 26:328.

paper · code

scMD single-cell DNA methylation reference panels
Epigenomics2024

scMD

Cell-type deconvolution using single-cell DNA methylation references.

Cai M, Zhou J, McKennan C, Wang J. Communications Biology, 7:1. Editors' Highlight

paper · code

HiDecon hierarchical cell-type tree with rare type highlighted
Deconvolution2024

HiDecon

Hierarchical deconvolution for accurate estimation of rare cell-type fractions.

Huang P, Cai M, Lu X, McKennan C, Wang J. Annals of Applied Statistics, 18(2):1178–1194.

paper · code

MIND deconvolution from bulk tissue to cell types
Deconvolution2020 / 2021

MIND & bMIND

Subject- and cell-type-specific gene expression from multi-measurement tissue data — frequentist and Bayesian.

Wang J, Devlin B, Roeder K. Bioinformatics, 36(3):782–788 (2020) · Wang J, Roeder K, Devlin B. Genome Research, 31(10):1807–1818 (2021).

MIND paper · bMIND paper · code

See the full publication list →

Join the lab · Collaborate

Prospective students

PhD & MS applicants

I am actively recruiting PhD students in Biostatistics and welcome inquiries from motivated students interested in research assistantships. If you enjoy statistical methodology, programming (R/Python), and working on biological data, we would love to hear from you.

  • Pitt Biostatistics & Health Data Science PhD program
  • Applications are reviewed annually
Email me about joining
Biomedical collaborators

Research collaboration

I collaborate with investigators across Alzheimer's disease, psychiatry, asthma, cancer, and related areas. Whether you have a single-cell or bulk omics dataset, a mediation/causal question, or a new study in design, I'm happy to discuss.

  • Method development driven by real biological problems
  • Grant co-investigator roles and paper collaborations welcome
Start a conversation

Recent news

  • 2026 Promoted to Associate Professor with tenure at Pitt.
  • 2026 Selected for the Health Sciences Leadership Academy for Early Career Faculty.
  • 2025 Chen Liu received the ASA Health Policy Statistics Section Student Paper Award for HMBART.
  • 2024 R21 funded — heterogeneous genetic effects and mediation in Alzheimer's disease.
  • 2024 Presented at the Senior Vice Chancellor's Research Seminar, University of Pittsburgh.
  • 2024 Manqi Cai defended her PhD dissertation (Delta Omega Dissertation Award).
  • 2023 R01 funded — statistical methods for population-level cell-type-specific analyses of tissue omics data in Alzheimer's disease.