Zhenke Wu

Assistant Professor of Biostatistics

University of Michigan
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zhenkewuobfuscate@gmail[punto]com

Bio:

Zhenke Wu’s research involves the development of statistical methods that inform health decisions made by individuals. He is particularly interested in scalable Bayesian methods that integrate multiple sources of evidence, with a focus on hierarchical latent variable modeling. We have applied our methods to estimate the etiology of childhood pneumonia, autoantibody signatures for subsetting autoimmune disease patients and to predict whether a user is engaged with mobile applications.

Zhenke has developed original methods and software that are now used by investigators from research institutes such as US CDC and Johns Hopkins, as well as site investigators from developing countries, e.g., Kenya, South Africa, Gambia, Mali, Zambia, Thailand and Bangladesh.

Zhenke completed a BS in Math at Fudan University in 2009 and a PhD in Biostatistics from the Johns Hopkins University in 2014 and then stayed at Hopkins for his postdoctoral training. Since 2016, Zhenke is Assistant Professor of Biostatistics, and Research Assistant Professor in Michigan Institute for Data Science (MIDAS) at University of Michigan, Ann Arbor.

Contact:

Department of Biostatistics
University of Michigan
1415 Washington Heights
4626 SPH-I (within Suite 4600)
Ann Arbor, MI 48109

Office Phone: +1-734-764-7067

Direction to my office: [.pdf]

Papers

A Caveat to Using Wearable Sensor Data for COVID-19 Detection: The Role of Behavioral Change after Receipt of Test Results

Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity

Integrating Sample Similarities into Latent Class Analysis: A Tree-Structured Shrinkage Approach

Clinical and Sociodemographic Factors Associated with Anticoagulant Use for Cancer Associated Thrombosis.

Probabilistic Cause-of-disease Assignment using Case-control Diagnostic Tests - A Hierarchcial Bayesian Latent Variable Regression Approach

Using a Bayesian Approach to Predict Patients’ Health and Response to Treatment

Anticoagulant Medication Adherence for Cancer Associated Thrombosis: A Comparison of LMWH to DOACs

A Robust Functional EM Algorithm for Incomplete Panel Count Data

A Bayesian Approach to Restricted Latent Class Models for Scientifically-Structured Clustering of Multivariate Binary Outcomes

Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment about Older Adults and COVID-19 Using Machine Learning.

Characterization of clinical progression of COVID-19 patients in Shenzhen, China

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes

Bayesian Weakly-Supervised Restricted Latent Class Models

Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns - A Micro-randomized Trial

Computational Analysis of Continuous Body Temperature Provides Early Discrimination of Graft-versus-Host Disease in Mice

Dynamic Tracking and Screening in Massive Datastreams

A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures

Micro-Randomized Trial

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study Results from The Michigan Genomics Initiative

Bayesian Estimation of Pneumonia Etiology: Epidemiologic Considerations and Applications to the Pneumonia Etiology Research for Child Health Study

Estimating AutoAntibody Signatures to Detect Autoimmune Disease Patient Subsets

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer; development of a prognostic model through a crowdsourced challenge with open clinical data

Predicting Survival Time for Metastatic Castration Resistant Prostate Cancer; An Iterative Imputation Approach

Nested Partially-Latent Class Models for Dependent Binary Data; Estimating Disease Etiology

Rejoinder to "Deductive Derivation and Turing-Computerization of Semiparametric Efficient Estimation"

Deductive Derivation and Turing-Computerization of Semiparametric Efficient Estimation

Partially Latent Class Models for Case–Control Studies of Childhood Pneumonia Aetiology

Estimation of Treatment Effects in Matched-Pair Cluster Randomized Trials by Calibrating Covariate Imbalance between Clusters

Lack of Response after Initial Chemoembolization for Hepatocellular Carcinoma: Does It Predict Failure of Subsequent Treatment?

Posts

Building R Package for Reproducibility: Why, When and How

Personal Tips for Academic Statisticians Working in OSX

Testing MathJax