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Research

Our faculty are consistently contributing to the national conversation through their research.

Faculty and students in the Division of Biostatistics are active in many areas of methodological and collaborative research, and regularly publish in high-impact statistics, biostatistics, and bio-medical journals.

Bayesian analysis: Haitao ChuJames Hodges, Joseph Koopmeiners, Thomas Murray, Cavan Reilly, Eric Lock, Lin Zhang

Causal inference: Haitao Chu, Jared Huling, Joseph Koopmeiners, Chap Le, Thomas Murray, Wei Pan, David Vock, Julian Wolfson, Baolin Wu, Tianzhong Yang

Clinical trials: Haitao Chu, John Connett, Anne Eaton, Lynn Eberly, Birgit Grund, Erika Helgeson, James Hodges, Joseph Koopmeiners, Chap Le, Xianghua Luo, Andrew Mugglin, Thomas Murray, James Neaton, Cavan Reilly, Kyle Rudser, David Vock

Statistical genetics & computational biology: Saonli Basu, Weihua Guan, Eric LockWei Pan, Cavan Reilly, Sandra Safo, Baolin Wu, Tianzhong Yang, Lin Zhang

Screening & diagnostic testing: Haitao Chu, Lynn Eberly, Joseph Koopmeiners, Chap Le

Machine learning: Saonli Basu, Lynn Eberly, Erika Helgeson, Jared HulingEric LockWei Pan, Ashley Petersen, Cavan Reilly, Sandra Safo, David Vock, Julian Wolfson

Medical imaging: Lynn Eberly, Mark Fiecas, Joseph Koopmeiners, Baolin Wu, Lin Zhang

Meta-analysis: Haitao Chu, James Hodges, Tianzhong Yang

Spatial statistics: Mark Fiecas, James Hodges, Lin Zhang

Survival analysis: Anne Eaton, Chap Le, Xianghua Luo, Thomas Murray, Kyle Rudser, David Vock

We pride ourselves on getting students involved in research early and often. Masters students complete a research-oriented Plan B project in collaboration with a faculty adviser. PhD students are involved in research assistantships starting from their first semester, and typically identify a dissertation adviser during the second year of the program. Dissertations follow the 3-paper model, so our students often graduate with multiple peer-reviewed publications.

Recent Student Project and Dissertation Titles:

  • Cynthia Basu, “Hierarchical Bayesian Models for the Pharmacokinetics & Pharmacodynamics of Lorenzo’s Oil”
  • Jeffrey Boatman, “Estimating the Causal Effect of Solid Organ Transplantation Treatment Regimes on Survival”
  • Kristen Cunanan, “Dose-Finding Using Hierarchical Modeling for Multiple Subgroups”
  • Abhirup Datta, “Environment Pollutants Interpolation Using Dynamic Nearest Neighbor Gaussian Process Model”
  • Caroline Groth, “Bayesian Model for Predicting Exposure in Multiple Exposure Groups”
  • Brandon Lee Koch, “Doubly Robust Estimation of Causal Treatment Effects with the Group Lasso”
  • Patrick Schnell, “A Bayesian Credible Subgroups Approach to Identifying Patient Groups with Positive Treatment Effect”
  • Hong Zhao, “Hierarchical Bayesian Approaches for Detecting Inconsistency in Network Meta-Analysis”
  • Xiaoyue Zhao, “Bayesian Hierarchical Modeling and Inference for Well-Mixed and Two-Zone Models in Industrial Hygiene”

Interdisciplinary research includes collaborations across the University of Minnesota, such as the Medical School, School of Nursing, Veterinary Science, the Carlson School of Management, and the Humphrey Institute for Public Affairs, as well as the Supercomputing Institute and Minnesota Population Center. The volume and scope of our collaborations are such that, on a per-faculty-member basis, the Division of Biostatistics is involved in more sponsored research than any other department or division at the University of Minnesota.

Many faculty in the Division of Biostatistics are members of the following collaborative research units:

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