Anru Zhang

Department of Biostatistics & Bioinformatics and Department of Computer Science, Duke University

I am a professor at Duke University working on the foundations, methodology, and applications of statistics and machine learning. My research interests span the following:

Statistical foundations

  • High-dimensional statistics
  • Computational complexity of inference

Methods & computation

  • Tensor data analysis
  • Nonconvex & Riemannian optimization
  • Markov (decision) processes

Generative AI

  • Generative models
  • Synthetic data

Science & health

  • Health informatics
  • Microbiome data analysis
  • Network analysis
  • Collaborative research
Anru Zhang
Google Scholar Duke profile

anru.zhang at duke dot edu

Background

I am a tenured full professor with joint primary appointments in the Department of Biostatistics & Bioinformatics (B&B) and the Department of Computer Science at Duke University, where I serve as Vice Chair for Research at Duke B&B. I hold secondary appointments in Duke Statistical Science and ECE.

I received my PhD from the University of Pennsylvania in 2015, advised by T. Tony Cai, and my bachelor's degree in mathematics from Peking University in 2010. Before joining Duke, I was an Assistant Professor of Statistics at UW–Madison.

Editorial service

Associate editor roles include The Annals of Statistics, the Theory & Methods and Applications & Case Studies sections of Journal of the American Statistical Association, Statistica Sinica, Statistics and Its Interface, ASA Discoveries, and Statistical Learning and Data Science.

Recognition

AMIA Fellow (2027), Leo Breiman Junior Award (2026), ASA Fellow (2026), COPSS Emerging Leader Award (2024), AMIA Data Science Outstanding Paper Award (2023), IMS Tweedie Award (2022), ASA Noether Junior Award (2021), Bernoulli Society New Researcher Award (2021), and NSF CAREER Award (2020).

For prospective students and researchers

Join the group

Our group is actively looking for motivated members to work on (1) methodology and theory in machine learning and statistics and/or (2) applications in AI for Health. Prospective PhD students may apply through Duke programs in Biostatistics & Bioinformatics, Computer Science, Electrical & Computer Engineering, or Computational Biology & Bioinformatics.

Selected news

  • Invited to deliver the keynote lecture at the University of Pittsburgh Biostatistics Research Day (March 2027).
  • Named a Fellow of the American Medical Informatics Association (AMIA).
  • Delivered a plenary lecture at the IFDS Research Expo, Institute for Foundations of Data Science, University of Wisconsin–Madison.
  • Elected Fellow of the American Statistical Association.
  • Short course on generative models at the Duke Industry Statistics Symposium.
  • Co-taught “Generative Models for Protein Structures and Biomedical Data” at ENAR.
  • Received the 2026 Leo Breiman Junior Award.
  • “Planner aware path learning in diffusion language models training” accepted as an oral presentation at ICLR 2026.
  • Teaching Excellence Recognition for BIOSTAT 915.

Books & outreach

Learning Statistics Through Pictures book series
Learning Statistics Through Pictures

A bilingual illustrated statistics book series for young readers, introducing statistical ideas through stories and visual examples. Explore the book series →