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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Eric Swanson

Eric Swanson

AI, Language, causation, context, ethics, ideology, values

Terra Sztain

improving computational models for allosteric inhibitor design and protein engineering

Stefan Szymanski

The economic and social analysis of sport
Nishil Talati

Nishil Talati

Hardware-software co-design for efficient and secure data analytics

Kean Ming Tan

Statistical Machine Learning, biomedical data
Jeremy M G Taylor

Jeremy M G Taylor

Statistical methodology for cancer research

Stephan F. Taylor

Neuroimaging and brain stimulation, diagnosis and psychiatric treatments

Stephanie Teasley

Sociotechnical systems for collaboration and successful learning outcomes

Misha Teplitskiy

computational methods, experimental methods, science of science
Jonathan Terhorst

Jonathan Terhorst

computational population genetics
Ambuj Tewari

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
Dawn Tilbury

Dawn Tilbury

Modeling and control for smart manufacturing, human-robot teaming
Sabina Tomkins

Sabina Tomkins

Computational social science, Political science, education, sustainability

Kentaro Toyama

including computer simulations of complex systems for policy-making, socio-economic development

Michael Traugott

Mass media and their impact on American politics