Seminars

The Division of Biostatistics & Health Data Science (BHDS) seminar series includes research-focused talks by visiting faculty from a wide range of institutions, and faculty from the University of Minnesota. All seminars are free and open to the public. Biostatistics students organize the Student Seminar Series, where students present and discuss their work in progress.

Date/Time/Location Name Affiliation Title
Wed, Sept 18, 2024
3:00 p.m.
University Office Plaza, Room 116
BHDS Faculty and Students University of Minnesota Division Working Groups Introduction
Wed, Oct 2, 2024
3:00 p.m.
University Office Plaza, Room 116
Lifeng Lin University of Arizona Monitoring Living Evidence for Research Synthesis
Wed, Oct 16, 2024
3:00 p.m.
University Office Plaza, Room 240
Julia Wrobel Emory University Modeling Trajectories Using Functional Linear Differential Equations
Wed, Oct 30, 2024
3:00 p.m.
University Office Plaza, Room 240
Haochang Shou University of Pennsylvania

Harmonization of Longitudinal Physical Activity Intensity Measures from Multiple Sources

Wed, Nov 6, 2024
3:00 p.m.
University Office Plaza, Room 116
Jiayi Tong Johns Hopkins Bloomberg School of Public Health Statistical Innovations Using Real World Data for Health System Performance Assessment
Mon, Nov 18, 2024
3:00 p.m.
University Office Plaza, Room 240
Jack Wolf University of Minnesota Efficient Treatment Effect Estimation by Jointly Modeling Multiple Endpoints
Wed, Nov 20, 2024
3:00 p.m.
University Office Plaza, Room 240
Charles Wolock University of Pennsylvania
Mon, Nov 25, 2024
3:00 p.m.
University Office Plaza, Room 240
Chao Cheng Yale University Semiparametric Causal Mediation Analysis in Cluster-Randomized Experiments
Mon, Dec 2, 2024
3:00 p.m.
University Office Plaza, Room 240
Ying Cui Stanford University
Wed, Dec 4, 2024
3:00 p.m.
University Office Plaza, Room 240
Mengxin Yu The Wharton School
Fri, Dec 6, 2024
1:30 p.m.
University Office Plaza, Room 116
Sijia Li Harvard University
Mon, Dec 9, 2024
3:00 p.m.
University Office Plaza, Room 240
Ye Tian Columbia University Regularized Fine-tuning in Representation Multi-task Learning: Adaptivity and Robustness
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