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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Kathleen M Bergen

Kathleen M Bergen

Field and geospatial methods for ecological systems, biodiversity and health

Sol Bermann

Big Data, Security, and law., data science, privacy, public policy

Halil Bisgin

Bioinformatics, Social Network Analysis, data mining
Anthony Bloch

Anthony Bloch

Control, Hamiltonian and Lagrangian Systems, gradient flows

Michael Boehnke

Statistical analysis of human genetic data
Elizabeth Bondi-Kelly

Elizabeth Bondi-Kelly

AI for social impact
Andrei Boutyline

Andrei Boutyline

quantitative methods for studying large-scale dynamics of cognitive representations
David Brang

David Brang

Multisensory, electrophysiology, machine learning, neuro-oncology, neuroscience

Christopher Brooks

Visualizing the interaction between learners and learning technology

Andrew Brouwer

Mathematical and statistical modeling for public health
Elizabeth Bruch

Elizabeth Bruch

Computer modeling of interactions between choices and environment

Sophia Brueckner

Brueckner leverages her background in algorithms and engineering to speculate and prototype preferred technological futures.

Fan Bu

Bayesian and computational statistics for analyzing large-scale and complex data
Ceren Budak

Ceren Budak

Computational social science

Matthew Bui

communities, data justice, social media
VAN HAI BUI

Van Hai Bui

optimization, power systems, reinforcement learning applications