Max Mintz

Professor, CIS

Research Interests

My research program focuses on developing robust algorithms for decision-making under uncertainty with applications to machine perception and robotics. Recent and current research topics include: robust fixed-geometry confidence regions for multivariate location parameters; algorithms for robust multisensor fusion; algorithms for set-valued state estimation with performance guarantees; applications of confidence sets in mobile robotics and computational vision.

Representative Publications

• Fan Zhang, Ben Grocholsky, Vijay Kumar, and Max Mintz. Cooperative Control for Localization of Mobile Sensor Networks. Lecture Notes in Control and Information Sciences, Volume 309, Springer-Verlag GmbH, 2004.
• Geoffrey Egnal, Max Mintz, and Richard P. Wildes. A Stereo Confidence Metric Using Single View Imagery with Comparison to Five Alternative Approaches. Image and Vision Computing. 22(12), 943-957, 2004.
  
• Geoffrey Egnal, Max Mintz, and Richard P. Wildes. A Stereo Confidence Metric Using Single View Imagery. CIPPRS/IAPR International Conference on Vision Interface, 2002. Runner-up for best student paper.
  
• Geoffrey Egnal, Max Mintz, and Kostas Daniilidis. Limiting the Search Range of Correlation Stereo Using Silhouettes. CIPPRS/IAPR International Conference on Vision Interface, 2002.
  
• Rajeev Alur, Calin Belta, Franjo Ivancic, Vijay Kumar, Max Mintz, George Pappas, Harvey Rubin, and Jonathan Schug. Modeling and Analyzing Biomolecular Networks. Computing in Science and Engineering. Vol. 4(1), pp. 20-31, 2002.
  
• G, Kamberova and M. Mintz. Minimax Rules Under Zero-One Loss for a Restricted Location Parameter. The Journal of Statistical Planning and Inference, (79)2 (1999) pp. 205-221. Reprint available as a PDF file.
  
• G. Kamberova, R. Mandelbaum, M. Mintz, and R. Bajcsy. Decision-Theoretic Approach to Robust Fusion of Location Data. Journal of the Franklin Institute, Vol. 336(2), (1999) pp. 269-284. Invited paper for a special issue on sensor fusion.
  
• R. Bajcsy and M. Mintz. The Separation of Photometry and Geometry Via Active Vision. In: The Confluence of Vision and Control, Lecture Notes in Control and Information Systems (LNCIS) Series. Edited by David Kriegman. Springer Verlag.
  
• G. Kamberova, R. Mandelbaum, and M. Mintz. Stereo Depth Estimation: A Confidence Interval Approach. Proceedings of the 1998 International Conference on Computer Vision.
  
• G. Kamberova, R. Mandelbaum, and M. Mintz. Statistical Decision Theory for Mobile Robotics: Theory and Application. Invited presentation at the special session on the theoretical basis of multisensor fusion and integration at the 1996 International Conference on Multisensor Fusion and Integration for Intelligent Systems, 9 December 1996, Washington DC.

Teaching

• CIT 592 - Mathematical Foundations of Computer Science
• CIT 596 - Theory of Computation

Contact Information

Office:	462 Levine/GRW
Phone:	215-898-7909
Email:	mintz at host cis.upenn.edu
Mail:	Computer and Information Science University of Pennsylvania 3330 Walnut Street Philadelphia, PA 19104