Around 280 U-M faculty members from over 60 departments are affiliated with MIDAS.

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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S. Sriram

Brand and product portfolio management

Stilian A. Stoev

Applied probability and statistics for stochastic processes

Quentin Stout

Scalable parallel algorithms for large scientific problems

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

Stochastic modeling, decision and control theory and applications to networks

Yuekai Sun

Statistical methodology for high-dimensional problems

Veera Sundararaghavan

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

Rie Suzuki

Social factors of health behaviors and health outcomes

Jeremy M G Taylor

Statistical methodology for cancer research

Stephanie Teasley

Sociotechnical systems for collaboration and successful learning outcomes

Jonathan Terhorst

computational population genetics

Ambuj Tewari

Statistical methods for sequential decision making in personalized health

Andrea Thomer

collaborative use of computational systems for scholarly research, data curation, scientific data practices