Walter Dempsey
Associate Professor
Develops statistical methods for digital and mobile health, including micro-randomized trials and adaptive interventions.
Walter Dempsey's lab at Michigan works on learning theory & optimization. 18 papers since 2023, 2 at top venues, mostly ICML and NeurIPS. 6 PhD students. 4 alumni. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 11%
- PhD students
- 6
- MS students
- 0
- alumni listed
- 4
Papers by yearfrom the lab homepage, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 7 papers2025 · T1 0
- 6 papers2024 · T1 1
- 4 papers2023 · T1 1
T1 venuesOtherVenues: ICML, NeurIPS
Research focuspaper titles that use each topic's words
- Learning theory & optimization2 papers
- mobile health2 papers
- statistical methods0 papers
- develops statistical0 papers
- adaptive0 papers
Paper list
From the lab homepage.
20261 paper
- Contemporary Clinical TrialsPractical considerations when designing an online learning algorithm for an app-based mHealth intervention
20257 papers
- BiometricsA Bayesian joint longitudinal-survival model with a latent stochastic process for intensive longitudinal data (opens in a new tab)
- PsychometrikaA Continuous-Time Dynamic Factor Model for Intensive Longitudinal Data Arising from Mobile Health Studies (opens in a new tab)
- BiometricsA meta-learning method for estimation of causal excursion effects to assess time-varying moderation (opens in a new tab)
- BiometricsData integration methods for micro-randomized trials (opens in a new tab)
- Journal of the American Statistical AssociationIncorporating Auxiliary Variables to Improve the Efficiency of Time-Varying Treatment Effect Estimation (opens in a new tab)
- Reinforcement Learning JournalNon-Stationary Latent Auto-Regressive Bandits (opens in a new tab)
- Electronic Journal of StatisticsSelective inference for sparse graphs via neighborhood selection
20246 papers
- Statistics in MedicineA latent variable approach to jointly modeling longitudinal and cumulative event data using a weighted two-stage approach
- Behavior Research MethodsDesign of experiments with sequential randomizations on multiple timescales: the hybrid experimental design (opens in a new tab)
- Science AdvancesExploring the Big Data Paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS) (opens in a new tab)
- Journal of the American Statistical AssociationNode-Level Community Detection within Edge Exchangeable Models for Interaction Processes (opens in a new tab)
- NeurIPS (T1)RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions
- Multivariate Behavioral ResearchSMART Binary: New Sample Size Planning Resources for SMART Studies with Binary Outcome Measurements (opens in a new tab)
20234 papers
- The Annals of Applied StatisticsAddressing selection bias and measurement error in COVID-19 case count data using auxiliary information (opens in a new tab)
- BiometrikaAssessing time-varying causal effect moderation in the presence of cluster-level treatment effect heterogeneity and interference (opens in a new tab)
- ICML (T1)CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data
- Journal of Computational and Graphical StatisticsRecurrent Event Analysis in the Presence of Real-Time High Frequency Data via Random Subsampling (opens in a new tab)
Where alumni went4 listed, 0% to industry
Industry 0Academia 4
Also to
- Harvard University
- Quantitative Marketing at Johns Hopkins University
- University of Cambridge
Apply to MichiganFall 2027
Michigan CSE Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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