500 MIDAS affiliate faculty members come from over 60 U-M departments, and include instructional (tenure / tenure track / lecturer), clinical and research track faculty.
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Bayesian methods, composite likelihood approach and missing data problems, efficient statistical computation algorithms, graphical models, latent source separation methods, network inference, ultrahigh-dimensional feature selection
ICU Vital Sign for Opioid Use Prediction
Cancer treatment communication, and quality of care, decision-making
Longitudinal analyses across multiple databases, population modeling.
Single cell and spatiotemporal analyses of healthy and diseased tissues
Smart and adaptive water systems
Analysis of Bach's organ music and performance
Simulation-based predictive design for new materials
Computational 3D genomics
Text disambiguation in scholarly data
Statistical inference for mechanistic models of infectious disease