Affiliated Faculty

500 MIDAS affiliate faculty members come from over 60 U-M departments, and include instructional (tenure / tenure track / lecturer), clinical and research track faculty.

Use this box to search by name, department, or other keyword. Use the filters below to search by major data science methodologies or applications.




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Jian Kang

Jian Kang

Bayesian methods, composite likelihood approach and missing data problems, efficient statistical computation algorithms, graphical models, latent source separation methods, network inference, ultrahigh-dimensional feature selection

Trishul Kapoor

ICU Vital Sign for Opioid Use Prediction

Steven J. Katz

Cancer treatment communication, and quality of care, decision-making
Daniel P. Keating

Daniel P. Keating

Longitudinal analyses across multiple databases, population modeling.

Evan Keller

Single cell and spatiotemporal analyses of healthy and diseased tissues
Branko Kerkez

Branko Kerkez

Smart and adaptive water systems

James Kibbie

Analysis of Bach's organ music and performance
John Kieffer

John Kieffer

Simulation-based predictive design for new materials
Minji Kim

Minji Kim

Computational 3D genomics

Jinseok Kim

Text disambiguation in scholarly data

Aaron A. King

Statistical inference for mechanistic models of infectious disease

Brendan Kochunas

Computational Nuclear Reactor Physics and Digital Twins

Ken Kollman

Political science, data infrastructure, elections, organizations

Barbara Koremenos

Scientific analysis of international law