The MIDAS affiliate faculty community consists of >360 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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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

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

Jessica Golbus

cardiology, digital interventions, machine learning

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

Alex Gorodetsky

Bayesian Inference, Decision making under uncertainty, Tensor Networks, Uncertianty Quantification

Andrew Grogan-Kaylor

Parenting behavior on child outcomes