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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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

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

Andrew Grogan-Kaylor

Parenting behavior on child outcomes

Yuanfang Guan

High-accuracy algorithms for predicting gene functions and networks

Emanuel Gull

Computational condensed matter physics

Samuel K Handelman

Multi-omics for precision health and population-level intervention outcome

Edward G. Happ

Information and communications technology