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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Jack D. Kalbfleisch
Analyzing failure time or event history data
Vineet Kamat
Construction; Robotics; Human-Robot Collaboration
Hyun Min Kang
Practical, accurate, and efficient methods for big data genome science
Trishul Kapoor
ICU Vital Sign for Opioid Use Prediction
Steven J. Katz
Cancer treatment communication, and quality of care, decision-making
Daniel P. Keating
Longitudinal analyses across multiple databases, population modeling.
Evan Keller
Single cell and spatiotemporal analyses of healthy and diseased tissues
Branko Kerkez
Smart and adaptive water systems
James Kibbie
Analysis of Bach's organ music and performance
John Kieffer
Simulation-based predictive design for new materials
Hun-Seok Kim
and efficient VLSI architectures for low-power/high-performance wireless communication, and machine learning systems, computer vision, novel algorithms, signal processing, system analysis
Jinseok Kim
Text disambiguation in scholarly data
Minji Kim
Computational 3D genomics
Aaron A. King
Statistical inference for mechanistic models of infectious disease
Brendan Kochunas
Computational Nuclear Reactor Physics and Digital Twins
Ken Kollman
Political science, data infrastructure, elections, organizations