Professor Max Mintz

Department of Computer and Information Science

 

Max Mintz
Rittenhouse Square
9/7/98

Basic Information:

  • Professor of Computer and Information Science

  • Office: 462 GRW, 200 S. 33rd Street

  • Office Telephone: (215) 898-7909

  • E-Mail: mintz@cis.upenn.edu

  • Postal Address: GRASP Laboratory, CIS Department, University of Pennsylvania, 200 S. 33rd Street, Philadelphia, PA 19104

  • Office Hours (Fall Semester 2014):

    Function: Day: Time: Room:
    CIS 261 TBA TBA TBA
    Academic Advising (By Appointment) 462 GRW

Teaching:

  • CIS 160, Mathematical Foundations of Computer Science, summer 2014

    CIS 160 Home Page: http://www.cis.upenn.edu/~mintz/cis160/index.html

  • CIS 261, Discrete Probability, Stochastic Processes, and Statistical Inference, fall 2014

    CIS 261 Home Page: http://www.cis.upenn.edu/~mintz/cis261/index.html

  • One of the following four courses in the spring semester:

    • CIS 628, Decision Making Under Uncertainty
    • CIS 398, Quantum Computer and Information Science
    • CIS 399, An Experimental Course in CIS
    • ENM 603, Probability Theory

  • Short Courses: These short courses are offered in the GRASP Lab from time to time as demand warrants.

    • Quantum Computation
    • Statistical Decision Theory
    • Game Theory
    • Probability Theory and Stochastic Processes

    For current short course syllabi, see: http://www.cis.upenn.edu/~mintz/shortcourses/index.html

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.

Recent Research 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.



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