Affiliated Faculty

The MIDAS affiliate faculty community consists of over 450 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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Qing Qu

Deep Learning, Inverse Problems, Nonconvex Optimization, Representation Learning

Kevin Quinn

Empirical legal studies and statistical methodology

Jenny Radesky

Research on young children, mobile/interactive media, parents

Trivellore E. Raghunathan

Missing data in sample surveys and in epidemiological studies

Indika Rajapakse

The dynamics of human genome organization

Venkat Raman

Simulation of large scale combustion systems

Arvind Rao

Multi-modal decision algorithms that integrate clinical measurements

Jeffrey Regier

Bayesian models and deep learning for scientific applications

Rudy J. Richardson

Molecular modeling, drug discovery, toxicology

Elizabeth F. S. Roberts

Developing methods for understanding domestic water infrastructures as “socio-techno-bio systems”

Daniel Romero

Empirical and theoretical analysis of social and information networks

Elliott Rouse

Wearable robotics, actuator design, biomechanics, exoskeletons, robotic prostheses, user preference and psychophysics

Michael Rubyan

Responsive Platform Design and Data Analytics around Health System Communication

Joseph Ryan

Big data tools for child welfare and juvenile justice

Greg Rybarczyk

Causal mechanisms that influence travel patterns and urban dynamics