The MIDAS affiliate faculty community consists of over 450 U-M faculty members from over 60 departments.
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Digging into data on science and academic careers
Fast and scalable algorithms for differential and integral equations on complex moving geometries
Use Data Science to promote high-value care in low resource settings.
Nils G. Walter
Intracellular single molecule, high-resolution localization
Natural language processing
two-sided markets and antitrust policy.
Civil and Environmental Engineering
AI in Education, Data Science Education, Human-Computer Interaction, learning at scale
Large-scale probabilistic machine learning, causal inference, machine learning for science
Models and methodologies for complex biomedical data
Simultaneous monitoring and processing of a large number of physiological parameters
Understanding biotic responses to global change
Analytical properties of interacting particle systems