Mark D. Happel is the Supervisor of the Data Science and Machine Learning Section in the Air and Missile Defense Sector (AMDS) of the Johns Hopkins University Applied Physics Laboratory (APL), where he performs machine learning, statistical pattern recognition, and signal processing research and development tasks. His recent projects have focused on pattern classification in time series data, distributed reinforcement learning, and infrared video processing.  

He is currently an instructor in the JHU’s Engineering for Professionals (EP) programs. Prior to this, he was an associate professorial lecturer in computer science at the George Washington University, where he taught both graduate-level and undergraduate-level artificial intelligence and machine learning courses for 10 years.  

Before coming to APL, Happel performed science and technology policy research at the RAND Corporation and both neuroscience and artificial intelligence research at the MITRE Corporation. He also developed real-time, safety-critical jet engine control software at GE Aircraft Engines and performed digital hardware design and test at Northern Telecom, Inc. His first professional experience was as a nuclear-trained submarine officer in the U.S. Navy, serving as the Reactor Controls Officer, Sonar Officer, and Weapons Officer onboard USS PHOENIX (SSN702).

Happel earned a BSEE degree in electrical engineering from the U.S. Naval Academy; an MSE degree in electrical engineering from the University of Central Florida; and a DSc degree in computer science from the George Washington University. 

Education History

  • B.S.E.E. Electrical Engineering, United States Naval Academy
  • M.S.E. Electrical Engineering, University of Central Florida
  • D.Sc. Computer Science, The George Washington University

Work Experience

Senior Professional Staff, JHU Applied Physics Laboratory


Happel, M.D., Spitaletta, J.A., Pohlmeyer, E.A., Hwang, G.M., Greenberg, A.M., Scholl, C.A., & Wolmetz, M., 2017. “National security and the assessment of individual credibility: Current challenges, future opportunities.” Johns Hopkins APL Technical Digest, 33(4), 303-313.

Haufler, A.J., Firpi, A., Goforth, M., Happel, M., Lee, A., Miller, J., Osorno, M., Rager, D., Rollend, D., Spitaletta, J., & Vogelstein, R.J., 2014. “A multi-modal examination of the biophysical signals of interpersonal trust in an interactive, computer-based gaming environment.” Washington DC: Society for Neuroscience (458.02/SS28).

Silberglitt, Richard, Philip S. Antón, Steven Berner, Paul DeLuca, Mark Happel, David R. Howell, Eric Landree, David S. Ortiz, Tim Webb, Shara Williams, 2010. Analyzing Emerging Technologies for Technology Security Concerns. Santa Monica, Calif.: RAND Corporation, DB-586-OSD. Not releasable to the general public.

Bonomo, James, Philip S. Antón, Mark Happel, Dick Hoffmann, Richard Mesic, Charles Nemfakos, Marc Viola, 2010. Planning for an Operational Assessment of Saber Focus (U). Santa Monica, Calif.: RAND Corporation, PM(L)-3157-NAVY. Not releasable to the general public.

Bonomo, J., Mesic, R., Matthews, V., Anton, P. S., Nemfakos, C., & Happel, M. D., 2008. Project SABER FOCUS: A Development Plan for Enhancing the Navy’s Irregular Warfare Capability. Santa Monica, CA: The RAND Corporation. Not releasable to the general public.

Happel, M. D., Webb, K. W., Sollinger, J., & Bradley, M., 2007. External Assessment of the Directorate of Intelligence Product Evaluation Methodology. Santa Monica, CA: The RAND Corporation. Not releasable to the general public.

Heckman, K. E., & Happel, M. D., 2006. “Mechanical Detection of Deception: A Short Review” in Educing information: Interrogation: Science and art—foundations for the future, ed. by Swenson, R.. Washington, DC: National Defense Intelligence College Press, 63-94.

Happel, M. D., 2005. “Neuroscience and the Detection of Deception”, Review of Policy Research, 22(5), 667-685.

Happel, M., Oertel, C., & Smith, D. B., 2005. “Geospatial Intelligence and the Neuroscience of Human Vision” in Optics and Photonics in Global Homeland Security, ed. by Saito, T. T., Proceedings of the SPIE Vol 5781. Bellingham, WA: SPIE, 98-108.

Happel, M., and Bock, P., 2001. “Overriding the Experts: A Fusion Method for Combining Marginal Classifiers”, International Journal on Artificial Intelligence Tools, 10(1&2), 157-179.

Happel, M., and Bock, P., 2000. “Analysis of a Fusion Method for Combining Marginal Classifiers” in Multiple Classifier Systems, ed. by Kittler, J., and Roli, F., Berlin: Springer-Verlag, 137-146.

Happel, M., and Bock, P., 2000. “Overriding the Experts: A Stacking Method for Combining Marginal Classifiers” in Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS-2000), ed. by Etheredge, J., and Manaris, B., AAAI Press, Menlo Park, CA, 66-70.

Happel, M., and Bock, P., 1996. “The Classification of Symbolic Concepts Using The ALISA Concept Module” in Proceedings of the Ninth International Symposium on Artificial Intelligence (ISAI-96), ed. by Soto, R., Sanchez, J., Campbell, M., and Cantu, F., IEEE Press, Piscataway, NJ, 170-179.

Happel, M., Pav, M., Jimenez, I., and Bock, P., 1995. “The Impact of Mode Filtering Sparse Images on the Reclassification Performance of the ALISA Geometry Module” in Architectures for Semiotic Modeling and Situation Analysis in Large Complex Systems: Proceeding of the 1995 ISIC Workshop, ed. by Albus, J., Meystel, A., Pospelov, D., and Reader, T., AdRem, Inc., Bala Cynwyd, PA., 314-321.

Happel, M., 1989. “The Use of Expert Systems in In-Circuit Testing” in ATE and Instrumentation (East) Proceedings, Boston, MA.

Happel, M., and B. Petrasko, 1988. “Ada Tools for the Description and Simulation of Digital Signal Processing Systems” in Proceedings of the Sixth National Conference on Ada Technology, U.S. Department of Commerce, Springfield, VA., 182-190.

Honors and Awards

  • Navy Achievement Medal (1985)

Professional Organizations

Society for Neuroscience
US Naval Institute
Association for the Advancement of Artificial Intelligence (AAAI)
Institute for Operations Research and the Management Sciences (INFORMS)