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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Carol Flannagan

Carol Flannagan

Models and data system of crash risk and avoidance

Danny Forger

Computer simulation and mathematical modeling of biological clocks

David Fouhey

Computer vision and machine learning

Robert J. Franzese Jr.

Spatial-econometric methods for interdependent processes

Johann Gagnon-Bartsch

High-throughput and high-dimensional data analysis

Andrzej T Galecki

Computational methods for correlated and over-dispersed data

Anne Ruggles Gere

Deeper conceptual learning for students and enhanced pedagogy for faculty

Anna Gilbert

Mathematical analysis, network and algorithms, probability

Brenda Gillespie

Censored data and clinical trials

Christopher E. Gillies

Predictive algorithms for critical care medicine

Pamela Giustinelli

The interplay of brain, and behavior during human development, biology

Sharon Glotzer

Computer simulation of nanosystems' self assembly

Oleg Gnedin

Formation and evolution of galaxies and star clusters

Bryan R. Goldsmith

Computional methods for sustainable chemical and energy production

Jason Goldstick

Spatial and temporal analysis of injury

Rich Gonzalez

Statistical learning and exploratory tools for biology and behavioral science