The MIDAS affiliate faculty community consists of >400 U-M faculty members from over 60 departments.


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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Kevin Stange

Education policy, Higher education, Labor economics

Anna G. Stefanopoulou

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

Joshua Stein

Enhancing Eye Care Using Big Data

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

Wenhao Sun

Materials Discovery and Design, Materials Informatics

Jing Sun

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

Veera Sundararaghavan

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

Rie Suzuki

Social factors of health behaviors and health outcomes

Stefan Szymanski

The economic and social analysis of sport

Kean Ming Tan

Statistical Machine Learning, biomedical data