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Joseph Godfrey

Collegiate Assistant Professor
  • Co-director, Systems Performance Laboratory
  • Director, Master of Engineering Administration Program

Lab website

Research Areas

Main Area: Management Systems Engineering

  • Social Choice (Computational Social Choice)
  • Game Theory (Cooperative Games)
  • Quantum Systems Engineering (Foundations, Workforce Development)
  • Systems Theory (Donabedian, Category Theory)
  • Engineering Economics (Theory of the Firm, Innovation)
  • Data Science (Automation, Agentic AI)
  • Market Research (GIS, Direct Marketing, Ethics)

  • Cert., CMMI Associate, ISACA / CMMI Institute, Pittsburgh, PA, 2024
  • Cert., Geographic Information Systems (GIS), Penn State University, University Park, PA, 2004
  • Graduate Coursework, Divinity, University of Notre Dame, Notre Dame, IN, 1987–1991
  • Ph.D., High Energy Physics, University of Notre Dame, Notre Dame, IN, 1987
  • B.S., Mathematics, University of Chicago, Chicago, IL, 1979

  • Management of Change, Innovation, and Performance in Organizational Systems
  • Economic Project Evaluation
  • Transfer and Application of Emerging Technology           
  • Engineering Program and Project Management
  • Introduction to Operations Research
  • Decision Analysis for Engineers
  • AI/ML for Systems
  • Enterprise Information Systems

  • Director of ISE Master of Engineering Administration program (the program continues to operate, but is not accepting new students)
  • Co-director of the Systems Performance Lab (SPL)

  • Supporting the development of a Ph.D. in ISE/Systems Engineering with a quantum focus.
  • Championing the development of a Virginia Quantum Network, consisting initially of three physical nodes in Northern Virginia, with at least two other 3-nodel components in Southwest and Southeast Virginia.
  • Collaborating with Virginia Tech Engineering Education (EngEd) on an NSF grant for quantum workforce development, as well as serving on committees for EngEd Ph.D. candidates.
  • Consulting for Dataline, one of the leading consumer cooperative database companies. My work for Dataline is especially focused on automation and integration of AI and Agentic AI capabilities.
  • Board of Directors of Azist Inc., an international company focused on IT support services for Microsoft and quality management certifications.

  • 2025 ASEM, October 8, System Analogies: A Categorical Framework Based on Donabedian’s SPO Model
  • 2026 Phase-Space Formulation of Shock-Containing Irrotational Barotropic Euler Flow. Molnar, Sandor M. et. al., Entropy (forth coming)
  • 2026 Koopman–von Neumann and Weyl–Wigner Phase-Space Formulation of Inviscid Euler Flows. Molnar, Sandor M. et. al., Entropy, Volume 28, Page 416
  • 2025 Balance equations for physics-informed machine learning. Molnar, Sandor M. et al., Heliyon, Volume 10, Issue 23
  • 2025 ASEM, September 24, A Theoretical Foundation for IDEF0 Using Category Theory
  • 2021 HVDMA, May 20, 01:00 PM, Podcast, Is Artificial Intelligence/Machine Learning Real? (Note that is before LLM’s burst on to the scene in 2202)
  • 2019 Dagstuhl Seminar, Application-Oriented Computational Social Choice