Mike Zmuda, Ph. D.

Research Highlights

  • Evolutionary Computation
  • Machine Learning
Portrait of Dr. Mike Zmuda

Associate Professor

Benton Hall, 201D


  • Ph.D.—Computer Science. Wright State University—1992
  • M.S.—Computer Science. Wright State University—1989
  • B.S.—Computer Science and Mathematics. Eastern Michigan Univ.—1987


Mike Zmuda’s research interests centers on the use of artificial intelligence and machine learning for the design of intelligent systems. Techniques such as evolutionary computation, particle filters, supervised learning, search, and image processing are techniques he has applied to problems. Application areas of current interest are pattern recognition in high-dimensional data, robot localization, and sensor fusion.


Academic Experience

  • Associate Professor, Miami University, Oxford, OH, 2003present
  • Assistant Professor, Miami University, Oxford, OH, 19972003
  • Adjunct Professor, Air Force Institute of Technology, 19931996
  • Adjunct Professor, Wright State University, 19911996 

Professional Experience

  • Principle Engineer, UMI, Dayton, OH, 19961997
  • Software Project Manager, Spectra Research, Centerville, OH, 1995–1996
  • Research Scientist, Wright-Patterson Air Force Base, Wright Laboratory, 1992–1995


  • "Extension of Hybrid Evolutionary Learning for Pattern Recognition Contract (HELPR) to Three-Dimensional Target Classification." U.S. Air Force contract. A $200,000 joint project with Prof. Mateen Rizki of Wright State University, 2002-2004
  • "Evolving Pattern Recognition Systems: A Multi-Faceted Approach." Air Force Contract #33615-99-C-1441 A $340,000 four year joint project with Prof. Mateen Rizki of Wright State University, 1998-2002 

Principal Publications


  • Eric Hodgson, Eric Bachmann, David Vincent, Michael Zmuda, David Waller, James Calusdian, "WeaVR: A Self-Contained and Wearable Immersive Virtual Environment Simulation System", Behavior Research Methods, 47(1), pp 296-307, 2015.
  • Michael Zmuda, Joshua Wonser, Eric Bachmann, and Eric Hodgson. Optimizing Constrained-Environment Redirected Walking Instructions Using Search Techniques. IEEE Transactions on Vision and Computer Graphics, 19(11), pp. 1872-1884, 2013.
  • Zmuda, M. and M. Hatch. “Scheduling Topics for Improved Student Comprehension of Recursion,” Computers in Education (48), pp 318-328, 2007.
  • Zmuda, M., M. Rizki, and L. Tamburino. “Mutating Real-Valued Vectors Using Angular Displacement” International Journal on Artificial Intelligence Tools, pp 509-526, 2003.
  • Zmuda, M., M. Rizki, and L. Tamburino. “An Evolutionary Learning for Synthesizing Multi-Class Pattern Recognition Systems,” Applied Soft Computing 2(4), pp. 269-282, 2003.
  • M. Rizki, Zmuda, M., and L. Tamburino. “Evolving Pattern Recognition Systems,” IEEE Transactions on Evolutionary Computation, pp. 594-609, Dec. 2002.
  • Zmuda, M. “A stochastic algorithm for approximating the soft morphological operators”. Optical Engineering, pp. 2746-2752, Dec., 2001.
  • Zmuda, M. and L. Tamburino, "Efficient Algorithms for Soft Morphological Operators,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1142-1147, Nov., 1996.
  • Zmuda, M., L. Tamburino, and M. Rizki, "An Evolutionary Learning System for Synthesizing Complex Morphological Filters," IEEE Transactions on Systems, Man, and Cybernetics, pp. 645-653, Aug., 1996.
  • Tamburino, L., M. Rizki, and M. Zmuda, "Generating Pattern Recognition Systems Using Evolutionary Learning," IEEE Expert, pp. 63-68, Aug., 1995.

Conference Papers

  • Michael Zmuda, Eric Bachmann, Eric Hodgson, Joshua Wonser. “Improved Resetting in Virtual Environments.” 2013 IEEE Virtual Reality Conference, pp. 91-92, 2013.
  • Eric Bachmann, Jeanette Holm, Michael Zmuda, Eric Hodgson. “Collision Prediction and Prevention in a Simultaneous Two-User Immersive Virtual Environment.” 2013 IEEE Virtual Reality Conference. pp.89-90, 2013.
  • Bachmann, E., J. Calusdian, E. Hodgson, X. Yun, and M. Zmuda. “Going Anywhere Anywhere – Creating a Low Cost Portable Immersive VE System,” Proceedings of the 17th International Computer Games Conference: AI, Interactive Media, Virtual Worlds, and Serious Games, 2012.
  • Claude C. Grigsby, Michael A. Zmuda, Derek W. Boone, Tyler C. Highlander, Ryan M. Kramer, and Mateen M. Rizki. “Differential profiling of volatile organic compound biomarker signatures utilizing a logical statistical filter-set and novel hybrid evolutionary classifiers.” SPIE Conference on Evolutionary and Bio-Inspired Computation: Theory and Applications, 2012.
  • M. Zmuda, A. Elesev, and Y. T. Morton. “Robot Localization Using RF and Inertial Sensors,” National Aerospace and Electronics Conference, 2008.
  • M. Zmuda and Y. T. Morton. “Calibrating Non-GPS Navigation Sensors for Use in Robot Localization,” Proceedings of the 2007 National Technical Meeting of Institute of Navigation, pp 1137-1146, 2007.
  • Zmuda, M., M. Rizki, and L. Tamburino. “Target Classification Using Morphological Features,” SPIE Conference for Synthetic Aperature Radar Imagery XI, pp. 321-331, 2004.
  • Zmuda, M., M. Rizki, and L. Tamburino. "Optimizing linear discriminants using evolutionary learning," Proceedings of the Artificial Neural Networks in Engineering Conference. ASME Press, 2002.
  • Tamburino, L., M. Rizki, and M. Zmuda, "HELPR Evolved Pattern Recognition Systems," World Multiconference on Systemics, Cybernetics, and Informatics Vol XIII, pp. 212-217, 2001.
  • Zmuda, M. "Recovering Tabular Information from ASCII Documents Using Evolutionary Programming," Proceedings of the Artificial Neural Networks in Engineering Conference. ASME Press, pp 189-195, 2001.
  • Wheeler, M. and M. Zmuda. "Processing Color and Complex Images Using Mathematical Morphology," Proceedings National Aerospace and Electronics Conference, pp. 618-624, 2000.
  • Zmuda, M., L. Tamburino, and M. Rizki. "Automated Synthesis of Pattern Recognition Systems" Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems. ASME Press, pp 381-386, 1999.