Around 260 U-M faculty members from over 60 departments are affiliated with the Michigan Institute for Data Science, providing them access to collaboration opportunities, support for research funding submissions, and updates on data science news and events at U-M and beyond.

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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Josh Pasek

New media, psychological processes and political behaviors

Sandun Perera

Supply chain and revenue management

Brian Perron

Services research for mental and substance use disorders

Mark Peterson

Physical activity epidemiology

Timothy Pletcher

Modeling and simulating the value and benefits of data sharing and policy trade offs

Keshav Pokhrel

Cancer epidemiology, quantile regression, time series forecasting

Stephen M. Pollock

Operations research and decision analysis

Atul Prakash

Design of operating systems and database mechanisms for sensitive data

Nicholson Price

How law shapes innovation in the life sciences

Kevin Quinn

Empirical legal studies and statistical methodology

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

Daniel Romero

Empirical and theoretical analysis of social and information networks