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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Anna G. Stefanopoulou

Batteries, Fuel-Cells, Model Multivariable Predictive Experimental Identification Engines
Joshua Stein

Joshua Stein

Enhancing Eye Care Using Big Data
Ryan Stidham

Ryan Stidham

Automated image analysis; medical image segmentation; clinical decision support systems; AI/ML clinical trials; Crohn's disease; ulcerative colitis; IBD
Stilian A.

Stilian A. Stoev

Applied probability and statistics for stochastic processes
James Stokes

James Stokes

leveraging ML for quantum many-body problems

Quentin Stout

Scalable parallel algorithms for large scientific problems
Martin J. Strauss

Martin J. Strauss

Randomized approximation algorithms for massive data sets

Wencong Su

Efficient management of a large number of devices through distributed intelligence
Vijay Subramanian

Vijay Subramanian

Stochastic modeling, decision and control theory and applications to networks

Jing Sun

adaptation, classification, estimation, modeling, predictive control, real-time optimization

Wenbo Sun

Uncertainty quantification, decision-making
Wenhao Sun

Wenhao Sun

Materials Discovery and Design, Materials Informatics

Yuekai Sun

Statistical methodology for high-dimensional problems

Veera Sundararaghavan

Integrated Computational Materials Engineering (ICME), Materials Informatics and Quantum Computing.

Z. Tuba Suzer-Gurtekin

Survey methodology

Rie Suzuki

Social factors of health behaviors and health outcomes