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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Atul Prakash

Design of operating systems and database mechanisms for sensitive data, Security, and adversarial machine learning., privacy

J.J. Prescott

Empirical Legal Studies

Nicholson Price

How law shapes innovation in the life sciences

Amiyatosh Purnanandam

Bank Risk, Default Risk, Equity in Finance, Financial Inclusion, Risk Management, Systemic Risk

Qing Qu

Deep Learning, Inverse Problems, Nonconvex Optimization, Representation Learning

Kevin Quinn

Empirical legal studies and statistical methodology
Dan Rabosky

Dan Rabosky

Computational macroevolution, biodiversity dynamics, machine learning, statistical theory
Photograph of Alison Davis Rabosky

Alison Davis Rabosky

Phenotypic innovation, the evolution of complex traits

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