Affiliated Faculty

MIDAS works to foster interdisciplinary research collaboration across campus with our community of 550 affiliate faculty members, who 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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Jaerock Kwon

Artificial Intelligence, autonomous vehicles, machine learning, neural network, robotics

Rahul Ladhania

Machine learning and causal inference in health

Sara Lafia

Data discovery, reuse and curation
Jeffrey C. Lagarias

Jeffrey C. Lagarias

Number theory, dynamical systems, optimization
Carl Lagoze

Carl Lagoze

Interoperability in information systems

Zach Landis-Lewis

Precision feedback for learning health systems
Ronald Gary Larson

Ronald Gary Larson

Computer simulations and statistical analysis of transport processes
Mariel Lavieri

Mariel Lavieri

personalized medicine, resource allocation, sequential decision making
Thuy Le

Thuy Le

cancer modeling, machine learning, mathematical model, tobacco use behaviors

Honglak Lee

Machine learning and its applications to artificial intelligence
Jon Lee

Jon Lee

Nonlinear discrete optimization
Sunghee Lee

Sunghee Lee

Cross-cultural research, Minority health, Survey methodology
Peter Lenk

Peter Lenk

Bayesian methods and data mining
Corey Lester

Corey Lester

Improving medication use with artificial intelligence
Margaret C. Levenstein

Margaret C. Levenstein

Computational social science

Elizaveta Levina

Statistical inference on realistic models for network