Zhenke Wu Research

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

Here are my publication samples. My CV is here, contact info is here. My GitHub is here and Bio is here. A recent faculty profile is here.

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.

I am interested in the design and application of statistical methods that inform health decisions made by individuals, or precision medicine. My current focus is on latent variable and causal inference methods that can support disease etiology studies, medical diagnosis, and health policy evaluation. Broadly, the statistical goal is to discover simple latent structures that improve inferences and population parameters and individual latent states. I have also worked on causal inference methods 1) to evaluate novel treatment rules under special designs like matched-pair cluster randomized design, as these designs are useful for interventions that can only be applied at cluster level; and 2) to facilitate the inference for novel estimands in semiparametric models by automating and unifying the derivation of efficient influence functions (EIF) and ensuing estimation.

Currently a major focus of my work is on the analysis of multiple mixed-type longitudinal measurements with feedbacks in treatment assignments. I am working on hierarchical Bayesian methods to infer latent trajectories that represent individual disease progressions that have direct applications to childhood pneumonia etiology studies, analyses of electronic health records and claims data, and just-in-time adaptive interventions (JITAI) in mobile health (mHealth) studies.

Postdoc Openning

Advising: We are recruiting motivated and hard-working students interested in Bayesian methods and computation, graphical models and large-scale health data analytics. If you are interested in joining the group, please apply to Biostatistics at the University of Michigan, Ann Arbor. If you are an undergrad or grad student at the University of Michigan, and you are interested in any of the papers or projects listed on this website, send me an email with your interests and CV.

Working Groups

Research interests:

I collaborate closely with

Published 28 Jan 2021
Published 31 Dec 2020
Clinical and Sociodemographic Factors Associated with Anticoagulant Use for Cancer Associated Thrombosis.
Schaefer et al. (2021). Journal of Thrombosis and Thrombolysis. In Press
Published 16 Dec 2020
Published 23 Oct 2020
Published 22 Oct 2020
Published 20 Oct 2020
Published 25 Sep 2020
Published 21 Sep 2020
Published 04 Aug 2020
Published 27 Apr 2020

Huge congrats to Irena and Hera for passing their PhD qualifying exams!!

Posted 01 Sep 2020 by Zhenke Wu

Huge congrats to Mengbing for winning “Best Doctoral Qualifying Exam Award”.

Another huge congrats to Irena for winning a poster award today in the 2019 MIDAS Annual Symposium in the category of “Most Likely to Make an Impact in the Field” for her poster “Regression Analysis for Probabilistic Cause-of-disease Assignment using Case-control Diagnostic Tests: A Hierarchical Bayesian Approach”!

Way to go!!

Posted 15 Nov 2019 by Zhenke Wu

The Main PERCH paper appeared in The Lancet today. We developed novel integrative Bayesian methods here, here, here, and more recently, here. Also check out the open-source R pacakge baker.

The visualization of PERCH results can be found here.

A press release is here.

Posted 28 Jun 2019 by Zhenke Wu

Huge congrats to Tim for having successfully defended his thesis on sequential randomized trials motivated by mental health and online education problems!

Another huge congrats to Mengbing for finishing her MS degree in biostatistics!

Previliged to have worked with you together in the past two years. Way to go!

Posted 13 Jun 2019 by Zhenke Wu

Our two-year project “Bayesian Hierarchical Models for Using Mobile Technology to Individualize Care in Mental Health” is funded by Precision Health at University of Michgian for developing analytical capacities and software tools suitable for mobile data streams. It is motivated by an ongoing multi-institution study of depression among first year medical interns.

Posted 24 Oct 2018 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