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Hi, I’m Walter Dempsey 👋

I am an Assistant Professor of Biostatistics and an Assistant Research Professor in the d3lab located in the Institute of Social Research at the University of Michigan. My research focuses on Statistical Methods for Digital and Mobile Health. I list my statistical papers below. A full publication list can be found on Google Scholar.

Contact Me

Education
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    University of Chicago

    Department of Statistics

    Ph.D.

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    University of Michigan

    Department of Statistics

    Postdoctoral Research Fellow

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    Harvard University

    Department of Statistics

    Postdoctoral Research Fellow

I list my statistical papers below. A full publication list can be found on Google Scholar.

  1. Node-level community detection within edge exchangeable models for interaction processes
    Zhang, Yuhua, and Dempsey, Walter
    2022
  2. Recurrent event analysis in the presence of real-time high frequency data via random subsampling
    Dempsey, Walter
    2022
  3. CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data.
    Zhang, Yuhua, and Dempsey, Walter H.
    In Proceedings of the 34th International Conference on Machine Learning 2023
  4. Design of experiments with sequential randomizations on multiple timescales: the hybrid experimental design
    Nahum-Shani, I., Dziak, J.J., Venera, H., Pfammatter, A., Spring, B., and Dempsey, W.
    Behav Res 2023
  5. Addressing selection bias and measurement error in COVID-19 case count data using auxiliary information
    Dempsey, Walter
    Annals of Applied Statistics (Forthcoming) 2022
  6. Assessing time-varying causal effect moderation in the presence of cluster-level treatment effect heterogeneity and interference
    Shi, J, Wu, Z, and Dempsey, W
    Biometrika 2022
  7. Kernel Multimodal Continuous Attention
    Moreno, Alexander, Wu, Zhenke, Nagesh, Supriya, Dempsey, Walter, and Rehg, James M
    In Advances in Neural Information Processing Systems 2022
  8. A Geometry-Driven Longitudinal Topic Model
    Wang, Yu, Hougen, Conrad, Oselio, Brandon, Dempsey, Walter, and Hero, Alfred
    Harvard Data Science Review 2021
  9. Hierarchical Network Models for Exchangeable Structured Interaction Processes
    Dempsey, Walter, Oselio, Brandon, and Hero, Alfred
    Journal of the American Statistical Association 2022
  10. A Robust Functional EM Algorithm for Incomplete Panel Count Data
    Moreno, Alexander, Wu, Zhenke, Yap, Jamie Roslyn, Lam, Cho, Wetter, David, Nahum-Shani, Inbal, Dempsey, Walter, and Rehg, James M
    In Advances in Neural Information Processing Systems 2020
  11. Exchangeable Markov multi-state survival processes
    Dempsey, W
    Stat Sin 2021
  12. A Statistical Framework for Modern Network Science
    Crane, Harry, and Dempsey, Walter
    Statistical Science 2021
  13. The stratified micro-randomized trial design: Sample size considerations for testing nested causal effects of time-varying treatments
    Dempsey, Walter, Liao, Peng, Kumar, Santosh, and Murphy, Susan A.
    The Annals of Applied Statistics 2020
  14. Relational exchangeability
    Crane, Harry, and Dempsey, Walter
    Journal of Applied Probability 2019
  15. Just-in-Time but Not Too Much: Determining Treatment Timing in Mobile Health
    Liao, Peng, Dempsey, Walter, Sarker, Hillol, Hossain, Syed Monowar, al’Absi, Mustafa, Klasnja, Predrag, and Murphy, Susan
    Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2018
  16. Survival models and health sequences
    Dempsey, Walter, and McCullagh, Peter
    Lifetime Data Anal 2018
  17. Edge Exchangeable Models for Interaction Networks
    Crane, Harry, and Dempsey, Walter
    Journal of the American Statistical Association 2018
  18. Exchangeable Markov survival processes and weak continuity of predictive distributions
    Dempsey, Walter, and McCullagh, Peter
    Electronic Journal of Statistics 2017
  19. iSurvive: An Interpretable, Event-time Prediction Model for mHealth
    Dempsey, Walter H., Moreno, Alexander, Scott, Christy K., Dennis, Michael L., Gustafson, David H., Murphy, Susan A., and Rehg, James M.
    In Proceedings of the 34th International Conference on Machine Learning 2017
  20. Randomised trials for the Fitbit generation
    Dempsey, Walter, Liao, Peng, Klasnja, Pedja, Nahum-Shani, Inbal, and Murphy, Susan A.
    Significance 2015
  21. Multiresolution analysis on the symmetric group
    Kondor, Risi, and Dempsey, Walter
    In Advances in Neural Information Processing Systems 2012

A list of recent courses that I have taught at the University of Michigan.

BIOSTAT617

01/01/2019 - 06/30/2023

Theory and Methods in Survey Design. Theory underlying sample designs and estimation procedures commonly used in survey practice. The latest version of the course can be found on Canvas

BIOSTAT629

08/30/2019 - 08/30/2020

Case Studies In Health Big Data. A project-based course that integrates all competencies learned in the Health Data Science Curriculum to provide a culminating research experience. Students work on two to three health big data projects, through which they learn to identify scientific objectives and analytical strategies and report findings through oral presentation and written documents. The latest version of the course can be found on Canvas

A list of recent graduate students and postdoctoral research fellows.

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Hera Shi
Graduated, 2023. Postdoctoral Research Fellow at the University of Cambridge with Qingyuan Zhao. Worked on statistical methods for time-varying treatment effects in the context of micro-randomized trials.
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Yuhua Zhang
Graduated, 2023. Postdoctoral Research Fellow at Harvard University with Jukka-Pekka Onnela. Worked on statistical methods for network data.
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Madeline Abbott
PhD Student. Working on statistical methods for intensive longitudinal data arising mobile health trials, specifically latent variable models and joint models with recurrent event processes.
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Easton Huch
PhD Student. Working on robust Bayesian methods for causal inference with applications to time-varying effect estimation in mobile health studies.

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