John Burkhardt, Ph.D.

Professor
Mechanical & Nuclear Engineering Department
United States Naval Academy
590 Holloway Road
Annapolis, MD 21402-5042
(410) 293-6507
burkhard@usna.edu

• Doctor of Philosophy, Theoretical and Applied Mechanics

• Master of Science, Theoretical and Applied Mechanics

• Bachelor of Engineering, Civil Engineering

• Machine Learning
• Stochastic Wave Propagation
• Nondestructive Testing
• Acoustics
• Vibrations
• Ultrasonics
• Atmospheric Turbulence

• Professor, United States Naval Academy (August 2021 - Present)
• Associate Professor, United States Naval Academy (August 2002 – July 2021)
• Assistant Professor, United States Naval Academy (August 1998 – July 2002)
• Assistant Professor, Purdue University at Fort Wayne (August 1995 – July 1998)

• Jellen, C., Nelson, C., Brownell, C., & Burkhardt, J. (2024). Effective benchmarks for optical turbulence modeling. Artificial Intelligence for the Earth Systems, 3(4), e240003.
• Jellen, C., Nelson, C., Brownell, C., & Burkhardt, J. (2024). Long-term measurement and characterization of boundary layer optical turbulence. Journal of the Optical Society of America A, 41(6), B65-B72.
• Jellen, C., Nelson, C., Burkhardt, J., & Brownell, C. (2023). Hybrid optical turbulence models using machine-learning and local measurements. Applied Optics, 62(18), 4880-4890.
• Jellen, C., Oakley, M., Nelson, C., Burkhardt, J., & Brownell, C. (2021). Machine-learning informed macro-meteorological models for the near-maritime environment. Applied Optics, 60(11), 2938-2951.
• Jellen, C., Nelson, C., Brownell, C., Burkhardt, J., & Oakley, M. (2020). Measurement and analysis of atmospheric optical turbulence in a near-maritime environment. IOP SciNotes, 1(2), 024006.
• Jellen, C., Burkhardt, J., Brownell, C., & Nelson, C. (2020). Machine learning informed predictor importance measures of environmental parameters in maritime optical turbulence. Applied Optics, 59(21), 6379-6389.
• Burkhardt, J. (2020). Bayesian parameter inference of explosive yields using Markov chain Monte Carlo techniques. International Journal of Mathematical Science and Computing, 6(2), 1-17.
• Burkhardt, J. (2019). Determination of the conductivity and thickness of conductive layers on conductive base materials. Advances in Mechanical Engineering, 11(7), 1687814019854234.

• United States Government Meritorious Service Medal (2006)