The MIDAS affiliate faculty community consists of over 420 U-M faculty members from over 60 departments.
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Analyzing failure time or event history data
Practical, accurate, and efficient methods for big data genome science
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
Cancer treatment communication, and quality of care, decision-making
Communicating uncertainty, and personal informatics, usable statistics
Longitudinal analyses across multiple databases, population modeling.
Single cell and spatiotemporal analyses of healthy and diseased tissues
Smart and adaptive water systems
Search-based software engineering and software refactoring
Analysis of Bach's organ music and performance
Simulation-based predictive design for new materials