Dr. Michele Van Dyne, PhD
Professor and Department Head
B.S. University of Montana, 1981
M.S. University of Montana, 1985
Ph.D. University of Kansas, 2003
Contact Information
mvandyne@mtech.edu
(406)-496-4855
Museum 204B
Academic Interests
Artificial intelligence in general, machine learning in particular
Mutli-agent systems, both cooperative and competitive
Robotics
Image processing
Personal Highlights
I grew up in Montana, and after almost 20 years away, living in the Midwest and doing applied research in artificial intelligence, I am very thankful to be back home. I enjoy hiking, skiing, camping, kayaking, and Montana in general. I also like to read, and am in a book club named Almost Famous. I love living in the country and watching the deer out my windows.
- Publications:
Schahczenski, C.; Van Dyne, M. 2019. “Easing the Burden of Program Assessment: Web-based Tool Facilitates Measuring Student Outcomes for ABET Accreditation”, Proceedings of the Hawaii International Conference on System Sciences, Jan. 7-11, 2019, Grand Wailea, Maui, HI.
Van Dyne, M.; Tsatsoulis, C. 2014. “Software Architecture for a System Combining Artificial Intelligence Approaches for Ground Station Scheduling”, Proceedings of the 18th International Conference on Computers (CSCC ‘14), July 17-21, 2014, Santorini, Greece, pp. 71-76.
Van Dyne, M; Braun, J. 2014. ”Effectiveness of a Computational Thinking (CS0) Course on Student Analytical Skills”, Proceedings of the Special Interest Group on Computer Science Education (SIGCSE ’14), March 5-8, 2014, Atlanta, GA.
Tsatsoulis, C.; Van Dyne, M. 2014. “Integrating Artificial Intelligence Techniques to Generate Ground Station Schedules”, Proceedings of the 2014 IEEE Aerospace Conference, March 1-8, 2014, Big Sky, MT.
Van Dyne, M; Fjermestad, J. 2012. ”Robotics in Education: A Tool for Recruiting, Engaging, Retaining and Educating Students”, Proceedings of the 12th WSEAS International Conference on Robotics, Control and Manufacturing Technology (ROCOM ’12), Apr. 18-20, Rovaniemi, Finland, pp. 196-201.
Van Dyne, M.; Tsatsoulis, C. 2012. “An Inferential System for Determination of Candidate Crash Sites for Search and Rescue Operations”, Proceedings of the 2012 IEEE Aerospace Conference, March 2012, Big Sky MT.
Fortier, N.; Van Dyne, M. 2011. ”A genetic algorithm approach to improve automated music composition”, International Journal of Computers, Issue 4, Vol. 5, pp. 525-532.
Fortier, N.; Van Dyne, M. 2011. ”Artificial Creativity: Improving on algorithmic music composition using genetic algorithms”, Proceedings of the 15th WSEAS International Conference on Computers, Corfu Island, Greece, Jul. 15-17, pp. 418-423.
Van Dyne, M.; Tsatsoulis, C. 2011. “Effect of agent decommitment in a target tracking domain”, Proceedings of the 2011 IEEE Aerospace Conference, Big Sky, MT, Mar. 5-12.
Van Dyne, M.; Tsatsoulis, C. 2010. “A comparison of agent decommitment techniques in a real-time environment”, Proceedings of the 9th Conference on Artificial Intelligence, Knowledge Engineering, and Databases (AIKED 2010), University of Cambridge, UK, Feb. 20-22, pp. 271-279.
Goodwin, L.; Van Dyne, M.; Lin, S.; Talbert, S. 2003. “Data mining issues and opportunities for building nursing knowledge”, Journal of Biomedical Informatics, pp. 379-388, 36(4,5)
Tsatsoulis, C.; Van Dyne, M.; Fetterer, F. 1998. “A Methodology for Analyzing Lead Information from SAE Ice Type Images”, IEEE Transactions on Geoscience and Remote Sensing, vol. 36, no. 2, 647-660.
Barton, R.G.; Raile, M.; McCampbell, D.; Holt, C.; Van Dyne, M. 1997. “Laboratory Investigation of the Real-Time Heuristic Prediction of Hydrocarbon Emissions”, Proceedings of the 1997 International Conference on Incineration and Thermal Treatment Technologies, Oakland, CA, May 12-13.
Barton, R.G.; Raile, M.; McCampbell, D.; Van Dyne, M. 1997. “Real-Time Prediction of Hydrocarbon Emissions from Liquid Combustion Systems”, Proceedings of the Air Waste and Management Association 90th Annual Meeting and Exhibition, Toronto, Canada, June 8-13.
Van Dyne, M.; Tsatsoulis, C.; Thorp, J. 1994. “Using Inductive Machine Learning, Expert Systems, and Case Based Reasoning to Predict Preterm Delivery in Pregnant Women”, Proceedings of the Database and Expert Systems Applications Conference (DEXA), Springer-Verlag.
Van Dyne, M.;, Tsatsoulis, C. 1994. “An Experiment to Determine Improvements in Automated Problem Solving in a Complex Problem Domain”, Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, Lawrence Erlbaum and Associates.
Silveira, P.E.; Van Dyne, M.; Tsatsoulis, C. 1994. “Sea Ice Feature Matching from SAR Arctic Data Using Neural Networks”, Proceedings of the International Geoscience and Remote Sensing Symposium.
Van Dyne, M.; Woolery, L..; Grzymala-Busse, J.; and Tsatsoulis, C. 1994. “Using Machine Learning and Expert Systems to Predict Preterm Delivery in Pregnant Women”, Proceedings of the Tenth IEEE Conference on Artificial Intelligence Applications, Computer Society Press, Washington D.C.
Woolery, L.; Van Dyne, M.; Grzymala-Busse, J.; Tsatsoulis, C. 1994. “Machine Learning for Development of an Expert System to Support Nurses’ Assessment of Preterm Labor Risk” in Grobe, S.J. and Pluyter-Wenting, E.S.P. (eds.), Nursing Informatics: An International Overview for Nursing in a Technological Era, Elsevier Publishers, Amsterdam, pp. 357-361.
Van Dyne, M.; Tsatsoulis, C. 1993. “Extraction and Analysis of Sea Ice Leads from SAR Images”, Proceedings of the International Geoscience and Remote Sensing Symposium, Tokyo.
Woolery, L.; Summers, S.; Clifford, R.; Hill, D.; Davies, L.; Glasnapp, D.; Van Dyne, M.; Mansfield, R.; Crown, D.; Sauer, J. 1992. “Knowledge Acquisition for Assessment of Preterm Labor Risk in Pregnant Women”. Proceedings of Sigma Theta Tau’s International State of the Science Congress on Nursing Research and Utilization. Omnipress: Madison, WI, 188.
Van Dyne, M.; Schaefer, R.M. 1991. “CABPRO Case Study” in R. Maus, J. Keyes (eds.), The Handbook of Expert System Applications in Manufacturing, McGraw-Hill, New York, N.Y.
Schaefer, R.M.; Colmer, J.S.; and Miley (Van Dyne) M. 1988. “CABPRO: A Rule-Based Expert System for Process Planning of Assembled Multiwire Cables”, Proceedings of the Fourth Conference on Artificial Intelligence Applications, Computer Society Press, Washington D.C.
- Research:
Research Advisor, Montana Tech – Concurrency in a Real-Time Multi-User Simulation, 2014-2015
Research Advisor, Montana Tech – Using Genetic Algorithms as a Tool for Encryption, 2012-2013
Faculty Coordinator, Montana Tech – Human-Computer Interaction, NAO Robot, 2011-2012
Research Advisor, Montana Tech – Genetic Algorithms and Artificial Creativity through Music Composition, 2011
Research Advisor, Montana Tech – Signature Authentication Based on Feature Recognition, 2011
Principal Investigator, Montana Tech – Intelligent Multi-Agent Research Lab, 2008-2010
Research Advisor, Montana Tech – Student Retention in the Computer Science Department, 2008-2009
Faculty Coordinator, Montana Tech – Multi-Agent Lab Network for Competition in the Simulation League of RoboCup, 2008
Faculty Coordinator, Montana Tech – Genetic Algorithms for the Prediction of Preterm Labor, 2007-2008
Principal Investigator, IntelliDyne, Inc., NASA GSFC – An Inferential System for Determination of Candidate Crash Sites for Search and Rescue Operations, 2004
Consultant, Duke University, NLM – Informatics Tools and Medical Perinatal Knowledge Building, 2002-2003
Doctoral Dissertation, University of Kansas, DARPA – Negotiated Decommitment in a Collaborative Agent Environment, 2001-2003
Team Member, Lawrence Applied Research, USAF – Space Vehicle Service Request Scheduling Using Case-Based Reasoning and Utility Theory, 1998-2000
Team Member, Lawrence Applied Research, NASA GSFC – Operationalization of SI Algorithm for the Identification of Sea Ice Types, 1999
Team Member, Lawrence Applied Research, NASA JSC – Space Shuttle Redundancy Management Using Case-Based Reasoning and Utility Theory, 1997
Consultant, Midwest Research Institute – Hazardous Waste Emissions Prediction Using Vision and Neural Networks, 1997-1998
Consultant, Midwest Research Institute – Automated Identification of Larvae Using Vision and Neural Networks, 1994-1995
Principal Investigator, IntelliDyne, Inc., NIH – Using Case Based Reasoning to Enhance an Expert System in Predicting Preterm Delivery, 1993
Principal Investigator, IntelliDyne, Inc., NIH/NCNR – Using Inductively Learned Rules to Predict Preterm Delivery, 1992-1993
Research Assistant, University of Kansas, JPL – Extraction and Analysis of Sea Ice Leads from Synthetic Aperture Radar (SAR) Images, 1992-1993
Research Assistant, University of Kansas, NASA – Sea Ice Feature Matching from SAR Artic Data Using Neural Networks, 1993