Zhenke Wu Research

Name in Chinese: 吴振科 . Pronounced: “Jen-Kuh Wu”.

[Publications] [CV-overleaf] [CV-pdf] [Contact] [Bio]

[Google Scholar] [GitHub] [Twitter].

The best way to contact me is email. Direction to my office is here.

I am an Assistant Professor in the Department of Biostatistics at University of Michigan, with joint appointment as Research Assistant Professor in Michigan Institute for Data Science (MIDAS). I am also Faculty Associate in Quantitative Methodology Program, Survey Research Center of Institute for Social Research (ISR), University of Michigan.

Research Theme:

My research is motivated by biomedical and public health problems and is centered on the design and application of statistical methods that inform health decisions made by individuals, or precision medicine. Towards this goal, I focus on two lines of methodological research: a) structured Bayesian latent variable models for clustering and disease subtyping, and b) study design, causal and reinforcement learning methods for evaluating sequential interventions that tailor to individuals’ changing circumstances such as in interventional mobile health studies. I am committed to developing robust, scalable, and interpretable statistical methods to harness real-world, high-dimensional, dynamic data for individualized health. The methods and software developed so far have supported studies in diverse scientific fields including infectious disease epidemiology, autoimmune diseases, mental health, behavioral health, and cancer.


Advising: We are recruiting motivated and hard-working people interested in Bayesian methods and computation, graphical models, causal inference, sequential decision making, reinforcement learning and large-scale health data analytics. If you want to get involved, please say hi.

Check this out and send me an email if interested in collaborating!

AI in Science Postdoctoral Fellowship Program; The program will pay a competitive salary ($74,000 annually for 2022-23) plus benefits. Travel to funder’s AI in Science events will also be covered.

Working Group:

I collaborate closely with

Published 17 May 2023
Published 24 Apr 2023
Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies
Yoshida et al. (2023). Accepted. Conference on Health, Inference, and Learning (CHIL)
Published 11 Apr 2023
Published 27 Mar 2023
Published 13 Feb 2023
Published 03 Jan 2023
Published 21 Nov 2022
Doubly Inhomogeneous Reinforcement Learning
Hu et al. (2022+). Submitted.
Published 07 Nov 2022
Published 26 Oct 2022
Dynamic Survival Transformers for Causal Inference with Electronic Health Records
Chatha et al. (2022). NeurIPS Workshop on Learning from Time Series for Health.
Published 21 Oct 2022

Thrilled to receive tenure! Heartfelt gratitude to family, students, collaborators, mentors, and reviewers for your help in reaching this milestone. Truly honored to be part of the esteemed umich community.

Posted 18 May 2023 by Zhenke Wu

We are organizing the 2023 ICSA Applied Statistics Symposium, which will be held from Sunday, June 11 to Wednesday, June 14, 2023 in Ann Arbor, Michigan. I am co-charing the local organizing committee. Please consider attending!

Posted 28 Apr 2023 by Zhenke Wu

Congratulations to MS student Abby Loe who has been accepted into doctoral program at Michigan Biostat! She has been working on the intersections between machine learning and classical statistical time-to-event and recurrent event data analysis.

Posted 09 Apr 2023 by Zhenke Wu

Congratulations to PhD student Mengbing Li who has been selected to receive an Institute of Mathematical Statistics Hannan Graduate Student Travel Award. She will be highlighted in the upcoming IMS bulletin, social media pages, and during IMS presidential address at JSM in Toronto. Congrats, Mengbing!

Posted 29 Mar 2023 by Zhenke Wu

Washington Post, USA Today, CNN, New York Times, The Guardian covered our work on quantifing how many UTI’s in the US are likely from meat people consumed/came in contact with. For this, we developed a statistical method that combine phylogenetics and Bayesian latent class models for mobile genetic elements.

Posted 27 Mar 2023 by Zhenke Wu
Posted 11 Sep 2020 by Zhenke Wu
Posted 11 Jul 2019 by Zhenke Wu
Testing MathJax
This blog tests math compatibility on this site
Posted 01 Nov 2015 by Zhenke Wu