Max Mintz
Professor
Computer and Information Science (CIS)
Email | Personal Webpage | Research Webpage
Honors and Awards: Award for Teaching Excellence in the Hard Sciences from the Student Committee on Undergraduate Education - 2004
Research Expertise: Robotics | Sensor Fusion
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.
Member of:
Recent Publications 
- Refined methods for creating realistic haptic virtual textures from tool-mediated contact acceleration data, Culbertson, H. | Romano, J.M. | Castillo, P. | Mintz, M. | Kuchenbecker, K.J., Haptics Symposium 2012, HAPTICS 2012 - Proceedings, 2012
- Data integration and pattern-finding in biological sequence with TESS's Annotation Grammar and Extraction Language (AnGEL), Schug, J. | Mintz, M. | Stoeckert Jr., C.J., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007
- A stereo confidence metric using single view imagery with comparison to five alternative approaches, Egnal, G. | Mintz, M. | Wildes, R.P., Image and Vision Computing, 2004
- Modeling and analyzing biomolecular networks, Alur, R. | Belta, C. | Kumar, V. | Mintz, M. | Pappas, G.J. | Rubin, H. | Schug, J., Computing in Science and Engineering, 2002
- Decision-theoretic approach to robust fusion of location data, Kamberova, G. | Mandelbaum, R. | Mintz, M. | Bajcsy, R., Journal of the Franklin Institute, 1999