
Max Mintz
Professor, CIS (1998 - 2022)
Max’s research program focuses on developing a better understanding of the nature of good algorithms for decision-making under uncertainty, with applications to machine perception and robotics. Current research topics include the application of game theory and statistical decision theory for designing robust fixed-geometry confidence regions for multivariate location parameters, and algorithms for robust multisensor fusion and set-valued state estimation with performance guarantees. Max also works with applications of confidence sets for cooperative and noncooperative mobile robots.
Research Areas
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Research Areas
- Statistical Decision Theory
- Data-Driven Modeling and Estimation
- Multisensor Fusion