Distribution of MIDAS affiliate faculty by primary college, school, or unit.
Affiliated Faculty
Yearly faculty collaborations on grant proposals since 2018, facilitated by MIDAS. Image credit: Bernardo Modenesi (MIDAS Data Science Fellow), Beth Uberseder (MIDAS Research Manager), and Ken Reid (MIDAS Data Scientist).
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MIDAS works to foster interdisciplinary research collaboration across campus with our community of 550 affiliate faculty members, who come from over 60 U-M departments, and include instructional (tenure / tenure track / lecturer), clinical and research track faculty.
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Gary L. Freed
Immunization policy, health policy and health economics for children
Ayumi Fujisaki-Manome
Arctic Ocean, Great Lakes, Sea/lake ice, hydrodynamics, machine learning, numerical modeling
Johann Gagnon-Bartsch
High-throughput and high-dimensional data analysis
Andrzej T Galecki
Computational methods for correlated and over-dispersed data
Krishna Garikipati
Scientific machine learning, data-driven modeling
Lana Garmire
Applying data science for actionable transformation of human health
Vikram Gavini
Ab-initio calculations, DFT, electronic structure, exchange-correlation approximation, numerical methods
Irina Gaynanova
Data integration and machine learning in biomedical applications
David Gerdes
Studying the Solar System using advanced computational tools
Anne Ruggles Gere
Deeper conceptual learning for students and enhanced pedagogy for faculty
Maani Ghaffari
Autonomous Navigation, Equivariant Representation Learning, Geometric Estimation and Control, Robot Learning and Control, Robot Perception
Hamid Ghanbari
digital health solutions for atrial fibrillation
Eric Gilbert
social computing and social media research
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