Affiliated Faculty

520 MIDAS affiliate faculty members 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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Akbar Waljee

Use Data Science to promote high-value care in low resource settings.

Nils G. Walter

Intracellular single molecule, high-resolution localization
Lu Wang

Lu Wang

Natural language processing
Naisyin Wang

Naisyin Wang

Models and methodologies for complex biomedical data
Runzi Wang

Runzi Wang

built environment, landscape architecture, machine learning, stormwater management, stream water quality, urban hydrology

Wenche Wang

two-sided markets and antitrust policy.

Wentao Wang

Civil and Environmental Engineering

Xu Wang

AI in Education, Data Science Education, Human-Computer Interaction, learning at scale

Yixin Wang

Large-scale probabilistic machine learning, causal inference, machine learning for science
Kevin Ward

Kevin Ward

Simultaneous monitoring and processing of a large number of physiological parameters
Brian Weeks

Brian Weeks

Understanding biotic responses to global change
Joshua Welch

Joshua Welch

Machine learning for representing molecular cell states
Xiaoquan William Wen

Xiaoquan William Wen

Bayesian models and computation, Probabilistic graphical models
Brady West

Brady West

Measurement error in auxiliary variables and survey data

Jenna Wiens

Machine learning and data mining for healthcare data