Zhenke Wu

Principal Investigator

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. He also works on sequential decision making by developing new statistical tools for reinforcement learning and micro-randomized trials. He has developed methods to estimate the etiology of childhood pneumonia, cause-of-death distributions using verbal autopsy, autoantibody signatures for subsetting autoimmune disease patients, and to estimate time-varying causal effects of mobile prompts upon lagged physical, mental and behavioral health outcomes.

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. Zhenke is currently an Associate Professor of Biostatistics at University of Michigan, Ann Arbor, and a faculty affiliate in Michigan Institute for Data Science (MIDAS).

When not thinking about Statistics, you can often find me playing basketball, running, rock climbing, hiking, downhill skiing, or doing short-distance triathlon.

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 Bayesian Approach to Modeling Variance of Intensive Longitudinal Biomarker Data as a Predictor of Health Outcomes

Geometry-driven Bayesian Inference for Ultrametric Covariance Matrices

Random Forest for Dynamic Risk Prediction of Recurrent Events: A Pseudo-Observation Approach

Variance as a predictor of health outcomes:using subject-level trajectories and variability of sex hormones to predict body fat changes in peri- and post-menopausal women

Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy

Etiology of acute lower respiratory illness hospitalizations among infants in four countries

Multivariate Dynamic Mediation Analysis under a Reinforcement Learning Framework

ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization

Bayesian Nested Latent Class Models for Cause-of-Death Assignment using Verbal Autopsies Across Multiple Domains

Does the Dosing of Mobile-based Just-in-Time-Adaptive Self-Management Prompts Matter? Preliminary Findings from a Pilot Micro-Randomized Study for Caregivers

Incorporating Auxiliary Variables to Improve the Efficiency of Time-Varying Treatment Effect Estimation

A joint modeling approach to study the association between subject-level longitudinal marker variabilities and repeated outcomes

Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations

An Automatically-Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

A Reinforcement Learning Framework for Dynamic Mediation Analysis

A Robust Test for the Stationarity Assumption in Sequential Decision Making

Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies

Feasibility pilot trial for the Trajectories of Recovery after Intravenous propofol versus inhaled VolatilE anesthesia (THRIVE) Pragmatic Randomized Controlled Trial

Using source-associated mobile genetic elements to identify zoonotic extraintestinal E. coli infections

Layperson-Facilitated Internet-Delivered Cognitive Behavioral Therapy for Homebound Older Adults with Depression: Protocol for a Randomized Controlled Trial

Estimating Time-Varying Direct and Indirect Causal Excursion Effects with Longitudinal Binary Outcomes

Doubly Inhomogeneous Reinforcement Learning

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

Dynamic Survival Transformers for Causal Inference with Electronic Health Records

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

Using machine learning with intensive longitudinal data to predict depression and suicidal ideation among medical interns over time

Probabilistic Learning of Treatment Trees in Cancer

Kernel Multimodal Continuous Attention

Effectiveness of gamified competition in the context of mHealth intervention for medical interns: a clustered micro-randomized trial

An App-Based Just-in-Time-Adaptive Self-Management Intervention for Care Partners: The CareQOL Feasibility Pilot Study

Parental preferences for STI and cancer vaccines in the US and in China

Outcome Adaptive Propensity Score Methods for Handling Censoring and High-Dimensionality: Application to Insurance Claims

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes

Improving outcomes for care partners of persons with traumatic brain injury: Protocol for a randomized control trial of a just-in-time-adaptive self-management intervention

Reinforcement Learning in Possibly Nonstationary Environment

baker: An R package for Nested Partially-Latent Class Models

Vaccine hesitancy during the COVID-19 pandemic: a latent class analysis of middle-aged and older US adults

Factors associated with inferior vena cava placement and retrieval for patients with cancer associated thrombosis

Dynamic Statistical Inference in Massive Datastreams

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

Acceptability and feasibility of an app-based just-in-time-adaptive self-management intervention for care partners: Protocol for the CareQOL pilot trial

The Mobile Assistance for Regulating Smoking (MARS) Micro-Randomized Trial Design Protocol

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

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

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

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"

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?

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