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Dr. Brett J. Borghetti, Ph.D.

Professor of Computer Science

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Professor of Computer Science, (Promoted to Professor: 17 July 2022) Department of Electrical and Computer Engineering, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH. Expertise in artificial intelligence, machine learning and deep learning. Teaches graduate-level courses in machine learning, deep learning, discrete mathematics, data security, artificial intelligence, and algorithm design.  Directs and advises Masters and Ph.D.-level research for sensor exploitation, cybersecurity, and human machine-teaming in operational environments.  Provides technical consultation to Air Force, Department of Defense, and national organizations.    Current Research Focus: machine learning for physical science sensors (hyperspectral, seismic), cybersecurity and improving performance of teams of humans and machines.

Associate Professor of Computer Science, (Promoted to Associate Professor: 9 July 2017) Department of Electrical and Computer Engineering, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH. Expertise in artificial intelligence, machine learning and multi-agent systems. Teaches graduate-level courses in machine learning, discrete mathematics, data security, artificial intelligence, and algorithm design.  Directs and advises Masters and Ph.D.-level research for human state assessment in operational environments.  Provides technical consultation to Air Force, Department of Defense, and national organizations.    Current Research Focus: machine learning for physical science sensors (hyperspectral, seismic) and improving performance of teams of humans and machines.

Assistant Professor of Computer Engineering, (Civilian: Appointed 29 July, 2013) Department of Electrical and Computer Engineering, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH. Expertise in artificial intelligence, machine learning and multi-agent systems. Teaches graduate-level courses in machine learning, discrete mathematics, data security, artificial intelligence, and algorithm design.  Directs and advises Masters and Ph.D.-level research for human state assessment in operational environments.  Provides technical consultation to Air Force, Department of Defense, and national organizations.    Research Focus: improving performance of teams of humans and machines using human physiological measures to estimate cognitive state.

Deputy, Department of Electrical and Computer Engineering (2011), Computer Science and Engineering Division Chief (2010-2011) and Assistant Professor of Computer Science, (Military: Appointed August, 2008) Department of Electrical and Computer Engineering, Air Force Institute of Technology, Wright-Patterson AFB, OH. Expertise in artificial intelligence, machine learning and multi-agent systems. Teaches graduate-level courses in data security, discrete mathematics, artificial intelligence, and algorithm design.  Directs and advises Masters and Ph.D.-level research in multi-agent systems, computer-generated forces, and cyber situational awareness.  Provides technical consultation to Air Force, Department of Defense, and national organizations.  As Division Chief for Computer Science and Engineering (Feb 2010 - May 2011) handles scheduling of courses, manpower, student issues, and day-to-day operations of the division.  As Deputy Department Head (Jun 2011- Dec 2011), handles multiple department-level duties  and serves as Acting Department Head in the Head’s absence.

Education

Ph.D., Computer Science, University of Minnesota, Twin Cities, MN, August 2008, Dissertation: “Opponent Modeling in Interesting Adversarial Environments,” Advisor: Dr. Maria Gini
Concentration: Statistical Machine Learning

M.S., Computer Systems, Air Force Institute of Technology, WPAFB, OH, December 1996, Thesis: “Inference Algorithm Performance and Selection Under Constrained Resources,” Advisor: Dr. Eugene Santos, Jr.
Concentration: Artificial Intelligence

B.S., Electrical Engineering, Worcester Polytechnic Institute (WPI), Worcester, MA, May 1992
Concentration: Computer Engineering

Air Force Reserve Officer Training Corps, Commissioned Officer, USAF ROTC Detachment 340, WPI, Worcester, MA, May 1992

Awards

2021       AETC Winner of the AY2021 AETC Educator of the Year award (Civilian Category) 

2021       AFIT/EN GSEM Winner of the Ezra Kotcher Teaching Award (GSEM Nominee to AFIT)

2020       AFIT/EN GSEM 4th Quarter Winner (Teaching Excellence Tool team; Nominee to AFIT)

2020       AFIT/EN GSEM Winner of the AETC Educator of the Year award (Nominee to AFIT)

2019       AFIT/EN Teaching Excellence Award

2018       Eta Kappa Nu (HKN) Outstanding Instructor of the year for 2018 (awarded March 2019)

2017       AFIT/ENG Quarterly Award Department Winner – Civ III category, 1st Quarter 2017

2015       AETC Winner of AF STEM Outstanding Science and Educator Award for 2014 (AETC Nominee to AF)

2015       AFIT Faculty Research Fellows Program

2014       Eta Kappa Nu Outstanding Teacher of the year for 2014

2013       Air Force Achievement Medal (2nd Oak Leaf Cluster)

2012       Joint Service Commendation Medal (2nd Oak Leaf Cluster)

2012       AFIT Team of the Quarter, Sep-Dec, 2012

2012       AFIT Volunteer of the Quarter, Sept-Dec, 2012

2010       Military Officers Association of America Outstanding Military Faculty Award, CY2010

2010       AFIT Field Grade Officer of the quarter, July-Sept 2010

2009       AETC Winner of AF Outstanding Scientist of the year (Senior Military Category; AETC nominee to AF)

2005       Air Force Commendation Medal

2003       Air Force Meritorious Service Medal

2000       Joint Service Commendation Medal & Oak Leaf Cluster

1999       USSTRATCOM/J6 (Directorate) Company Grade Officer of the Quarter

1995       Air Force Achievement Medal

1992       Distinguished Graduate: Air Force Reserve Officer Training Corps

1992       Inducted: Eta Kappa Nu, Electrical Engineering Honor Society

1992       Inducted: Tau Beta Pi, National Engineering Honor Society

1988       Air Force Reserve Officer Training Corps Scholarship

Publications

* Denotes student, ** Denotes Research Assistant

Book Chapters

  1. Funke, G., Dye, G.*, Borghetti, B.J., Mancuso, V., Greenlee, E., Miller, B., Menke, L., Brown, R., and Vieane, A., “Development and Validation of the Air Force Cyber Intruder Alert Testbed (CIAT)”, Advances in human factors in cybersecurity, pp. 363-376. Springer, Switzerland, 2016.
    DOI 10.1007/978-3-319-41932-9_30
    https://www.researchgate.net/profile/Gregory_Funke/publication/305082248_Development_and_Validation_of_the_Air_Force_Cyber_Intruder_Alert_Testbed_CIAT/links/5a66439fa6fdccb61c5a71f6/Development-and-Validation-of-the-Air-Force-Cyber-Intruder-Alert-Testbed-CIAT.pdf
  2. Borghetti, B.J. and Gini, M., “Weighted Prediction Divergence for Metareasoning”, Metareasoning-thinking about thinking, M. Cox and A. Raja, Eds., (Chapter 16) MIT Press, Cambridge, MA, 2011 (ISBN-10 0-262-01480-7).

 Journal Publications

  1. Brinker, Markus W., Bickley, Abigail A., Borghetti, Brett J., Franz, Antony L., Goldblum, Bethany L., Whetzel, J., Bevins, James E., “Characterization of Nuclear Fuel Cycle Operations Using Convolutional Neural Network Analysis of High Frequency Magnetometer Data”, Journal of Defense Research and Engineering, (JDR&E), Vol 7, Issue 1, Pages 6-17, 2024. (DTIC Accession number ADC201733, published 26 Feb 2024). (S//NF)
  2. *Burt, Braden, Borghetti, Brett J., Franz, Anthony L., Holland, Darren E., and Bickley, Abigail A., “Application of Machine Learning for Classification of Nuclear Reactor Operational Status Using Magnetic Field Sensors”, special issue of Nuclear Security and Nonproliferation Research and Development, Journal of Nuclear Engineering (MDPI), 4, 723-731, 6 Dec 2023; https://doi.org/10.3390/jne4040045
  3. *Duncan, Mark C., Miller, Michael E., Borghetti, Brett J., “Analysis and Requirement Generation for Defense Intelligence Search: Addressing Data Overload through Human–AI Agent System Design for Ambient Awareness”, Systems Journal Special Issue "Design Methods for Human-Machine Teams” (MDPI), 11(12) 561, pp1-28, 29 Nov 2023; https://www.mdpi.com/2079-8954/11/12/561  (submission:  systems-2622760)
  4. *Choate, Jeffrey L., *Worth, Derek B., Nykl, Scott L., Taylor, Clark N., Borghetti, Brett J., and Schubert Kabban, Christine, “An Analysis of Precision: Occlusion and Perspective Geometry's Role in 6D Pose Estimation.” Neural Computing and Applications, vol 36, pp 1261-1281 (2024) SpringerLink (published 31 Oct 2023) https://doi.org/10.1007/s00521-023-09094-8 ; https://link.springer.com/article/10.1007/s00521-023-09094-8
  5. *Decker, Kevin T., Borghetti, Brett J., “Hyperspectral Point Cloud Projection for the Semantic Segmentation of Multimodal Hyperspectral and Lidar Data with Point Convolution-Based Deep Fusion Neural Networks,” Special Issue: Novel Approaches for Remote Sensing Image Processing, Applied Sciences Journal (MDPI),  13 (14), 8210, 13 July 2023, https://www.mdpi.com/2076-3417/13/14/8210 )
  6. *Hoecherl, Joseph C., Robbins, Matthew J., Borghetti, Brett J., and Hill, Raymond R., “Partially Autoregressive Machine Learning: Development and Testing of Methods to Predict United States Air Force Retention”., Journal of Computers and Industrial Engineering, volume 171, 1 Sep 2022 https://doi.org/10.1016/j.cie.2022.108424 
  7. Basrawi, Khaled, Dill, Richard, Borghetti, Brett J., Peterson Gilbert L., Lopez, Jennifer S., “Aircraft Identification from ADS-B Kinematic Data,” Journal of DoD Research & Engineering. DTIC, 5 (2), 31-43, 27 June, 2022 (Accession # AD1172011; CUI)
  8. *Decker, Kevin T., Borghetti, Brett J., “Composite Style Pixel and Point Convolution Based Deep Fusion Neural Network Architecture for the Semantic Segmentation of Hyperspectral and Lidar Data,” Special Issue Information Retrieval from Remote Sensing Images, Remote Sensing Journal (MDPI), Vol 14(9) pg 2113, 28 Apr 2022. https://doi.org/10.3390/rs14092113,  https://www.mdpi.com/2072-4292/14/9/2113 . 
  9. Koranek, Daniel F., Graham, Scott R., Borghetti, Brett J., and Henry, Wayne C., “Identification of Return-Oriented Programming Attacks Using RISC-V Instruction Trace Data” IEEE Access, Vol 10, pp 45347 - 45364, 25 Apr 2022, DOI: 10.1109/ACCESS.2022.3170479,  https://ieeexplore.ieee.org/document/9762913
  10. *Gutierrez del Arroyo, Jose A., Borghetti, Brett J., and Temple, Michael A., “Considerations for Radio Frequency Fingerprinting across Multiple Frequency Channels,” Sensors Journal, Special Issue on Radio Frequency Machine Learning (RFML) Applications (MDPI), volume 22, no 6: 2111, pp 1-21, 9 Mar 2022.
    https://www.mdpi.com/1424-8220/22/6/2111  
  11. *Langehaug, Tor J., Graham, Scott R., Schubert Kabban, Christine M., and Borghetti, Brett J., “MADFAM: MicroArchitectural Data Framework and Methodology,” IEEE Access, Vol 10, pp 23511-23531, 7 Mar 2022
    https://doi.org/10.1109/ACCESS.2022.3153313
  12. *Seik, Jason, Borghetti, Brett J., McClory, John W., and Bickley, Abigail A., “Application of an Artificial Neural Network to Elemental Assay Data for Nuclear Forensics Analysis,” Journal of Radiation Effects, Research and Engineering (JRERE), Vol 40, No. 1, March 2022. 
  13. *Kamrud, Alexander J., Borghetti, Brett, J., Schubert Kabban, C. M., and Miller, Michael E., “Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks”, Sensors Journal, Special Issue on EEG Signal Processing for Biomedical Applications 21(16), 5617, MDPI, 20 Aug 2021
    https://www.mdpi.com/1424-8220/21/16/5617 ; https://doi.org/10.3390/s21165617
  14. *Kamrud, Alexander J., Borghetti, Brett, J., Schubert Kabban, C. M., “The Effects of Individual Differences, Non-Stationarity, and the Importance of Data Partitioning Decisions for Training and Testing of EEG Cross-Participant Models”, Sensors Journal, Special Issue on Intelligent Biosignal Analysis Methods., 21(9), 3225, MDPI, 6 May 2021
    https://www.mdpi.com/1424-8220/21/9/3225 ; https://doi.org/10.3390/s21093225
  15. *Langehaug, Tor J., Borghetti, Brett J., and Graham, Scott R., “Classifying Co-resident Computer Programs Using Information Revealed by Resource Contention,” DTRAP: Journal of Digital Threats and Practices, Association for Computing Machinery, Vol 0, number ‘ja’, Accepted online, 29 April 2021   https://doi.org/10.1145/3464306
  16. *Lee, Andrew T., *Dallmann, William E., Nykl, Scott L., Taylor, Clark N., and Borghetti, Brett, J., “Long Range Pose Estimation for Aerial Refueling Approaches Using Deep Neural Networks” AIAA: Journal of Aerospace Information Systems, Vol. 17, No. 11 (11 Nov 2020), pp. 634-646 doi: doi/abs/10.2514/1.I010842 https://arc.aiaa.org/doi/10.2514/1.I010842
  17. *Westing, Nicholas M., Gross, Kevin C., Borghetti, Brett, J., Schubert Kabban, C. M., “Multimodal Representation Learning and Set Attention for LWIR In-Scene Atmospheric Compensation” IEEE Journal of Selected Topics In Applied Earth Observations and Remote Sensing, (IEEE Early Access, 28 Oct 2020).  DOI: 10.1109/JSTARS.2020.3034421. https://ieeexplore.ieee.org/abstract/document/9242299
  18. *Dickey, Joshua, T., Borghetti, Brett, J., Junek, William, and Martin, Richard “BazNet: A Deep Neural Network for Confident Three-component Backazimuth Prediction” Pure and Applied Geophysics, 9 Oct 2020 https://link.springer.com/article/10.1007/s00024-020-02578-x
  19. *Westing, Nicholas M., Gross, Kevin C., Borghetti, Brett, J., Martin, Jacob, and Meola, Joseph,  “Learning Set Representations for LWIR In-Scene Atmospheric Compensation” IEEE Journal of Selected Topics In Applied Earth Observations and Remote Sensing, 2 Apr 2020, Vol 13, pp 1438-1449
    https://ieeexplore.ieee.org/document/9055124
  20. *Dickey, Joshua, T., Borghetti, Brett, J., Junek, William, and Martin, Richard “Beyond Correlation: A Path-invariant Measure for Seismogram Similarity” Seismological Research Letters, 6 Nov 2019, Vol 91, pp 356-369
    DOI: 10.1785/0220190090  
    https://pubs.geoscienceworld.org/srl/article-pdf/doi/10.1785/0220190090/4862061/srl-2019090.1.pdf
  21. *Westing, Nicholas M., Borghetti, Brett, J., Gross, Kevin C., “Fast and Effective Techniques for LWIR Radiative Transfer Modeling: A Dimension Reduction Approach”, Remote Sensing (MDPI), 9 Aug 2019, Vol 11, issue 6, pp. 1866-1886, DOI: 10.3390/rs11161866
    https://www.mdpi.com/2072-4292/11/16/1866/htm
  22. *Dickey, Joshua T., Borghetti, Brett J., and Junek, William, “Improving Regional and Teleseismic Detection for Single-Trace Waveforms Using a Deep Temporal Convolutional Neural Network Trained with an Array-Beam Catalog”, Sensors (MDPI), 31 Jan 2019, Vol 19, issue 3, pp 597-618, DOI: 10.3390/s19030597
    https://www.mdpi.com/1424-8220/19/3/597
  23. *Curro, Joseph A., Raquet, John F., Borghetti, Brett J., “Navigation Using VLF Signals with Artificial Neural Networks” NAVIGATION, The Journal of the Institute of Navigation, 5 Dec 2018, pp. 549-561.  https://onlinelibrary.wiley.com/doi/epdf/10.1002/navi.264
  24. *Hefron, Ryan G., Borghetti, Brett J., Christensen, James C., Schubert Kabban, Christine M., Estepp, Justin R., “Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks,” Sensors (MDPI), Vol 18(5), 26 April 2018, Article Number 1339, pp 1-27.   DOI:10.3390/s18051339.
    http://www.mdpi.com/1424-8220/18/5/1339  
  25. Rusnock, C.F., and Borghetti, Brett J., “Workload Profiles: A continuous Measure of Mental workload”, International Journal of Industrial Ergonomics, Vol 63, Jan 2018, pp 49-64. https://doi.org/10.1016/j.ergon.2016.09.003   http://www.sciencedirect.com/science/article/pii/S0169814116301287
  26. *Hefron, Ryan G., Borghetti, Brett J., Christensen, James C., Schubert Kabban, Christine M., “Deep long short-term memory structures model temporal dependencies improving cognitive workload estimation,” Pattern Recognition Letters (Elsevier), Vol 94, 15 July 2017, pp 96-104. https://www.sciencedirect.com/science/article/pii/S0167865517301678
  27. Borghetti, B.J., Giametta, J.J*., & Rusnock, C.F., “Assessing Continuous Operator Workload with a Hybrid Scaffolded Neuroergonomic Modeling Approach,” Human Factors, Vol 59, No. 1, Feb 2017, pp 134-146. DOI: 10.1177/0018720816672308
    http://journals.sagepub.com/doi/abs/10.1177/0018720816672308  
  28. *Weller-Fahy, D. J.*, Borghetti, B.J., and Sodemann, A.A., “A Survey of Distance and Similarity Measures used within Network Intrusion Anomaly Detection”, IEEE Communication Surveys and Tutorials, vol. 17, no. 1, pp. 70-91, 11 July 2014, DOI 10.1109/COMST.2014.2336610
    https://ieeexplore.ieee.org/abstract/document/6853338
  29. **Sodemann, A.A., *Ross, M.P., and Borghetti, B.J., “A Review of Anomaly Detection in Automated Surveillance”, IEEE Transactions on System, Man, and Cybernetics Part C, vol. 42, No. 6, 12 December 2012,  pp 1257-1272.  DOI 10.1109/TSMCC.2012.2215319
    https://ieeexplore.ieee.org/abstract/document/6392472
  30. *Borowski, J., Hopkinson, K.,  Humphries J.,  Borghetti, B.J., “Reputation-Based Trust for a Cooperative Agent-Based Backup Protection Scheme” IEEE Transactions on Smart Grid, Vol 2, Issue 2, 5 April 2011, pp 287-301.
    DOI: 10.1109/TSG.2011.2118240
    https://ieeexplore.ieee.org/document/5740978
  31. *Weissgerber, K., Lamont, G.B., Borghetti, B.J., Peterson, G.L., “Determining Solution Space characteristics for Real Time Strategy Games and Characterizing Winning Strategies”, International Journal of Computer Games Technology, vol. 2011, 3 July 2011, pp 1-17. DOI:  10.1155/2011/834026.
    https://www.hindawi.com/journals/ijcgt/2011/834026/
  32. Thomas, R.W., Borghetti, B.J., Komali, R.S. Mahonen, P., “Understanding Conditions that Lead to Emulation Attacks in Dynamic Spectrum Access”  IEEE Communications Magazine, Vol 49 No. 3, 7 March 2011, pp 32-37.
    DOI: 10.1109/MCOM.2011.5723797
    https://ieeexplore.ieee.org/document/5723797
  33. Borghetti, B.J., “The Environment-Value of an Opponent Model”, IEEE Transactions on Systems, Man, and Cybernetics Part B, special issue on Game Theory, Issue 99, 3 Nov 2009 pp 1-11 (Print: Volume 40, No. 3 pp 623-633)
    DOI: 10.1109/TSMCB.2009.2033703
    https://ieeexplore.ieee.org/abstract/document/5308299

Refereed Conference Publications

  1. *Gallaher, Joshua P., *Kamrud, Alexander J., Borghetti, Brett J., “Detection and Mitigation of Inefficient Visual Searching”, Human Factors and Ergonomics Society (HFES) Annual Conference, 2020, (Virtual), 5-9 Oct 2020.
    https://journals.sagepub.com/doi/pdf/10.1177/1071181320641015

  2. *Crow, David R., Graham, Scott R., Borghetti, Brett J., Sweeney, Patrick J., “Empirical Dynamic Modeling as a Basis for an Intrusion Detection System” 14th International Conference on Critical Infrastructure Protection (IFIP), Arlington, VA, USA, Mar 2020
  3. *Villarreal, Micah N., *Kamrud, Alexander J., Borghetti, Brett J., “Confirmation Bias Estimation from Electroencephalography with Machine Learning”, Human Factors and Ergonomics Society (HFES) Annual Conference, 2019, Seattle, WA, 28 Oct-1 Nov 2019.
  4. Skouson, Mark B., Borghetti, Brett J., Leishman, Robert C., “Ursa: A Neural Network for Unordered Point Clouds Using Constellations”, Computer Vision Conference (CVC) 2019, Las Vegas, NV, 25-26 Apr 2019.
  5. *Sinn, Yong U., Hopkinson, Kenneth M., Borghetti, Brett J., Steward, Bryan J., “IR Small Target Detection And Prediction With ANNs Trained Using ASSET”, IEEE Aerospace Conference, Big Sky, MT, 2-9 Mar 2019
  6. *Sample, Kenneth, Lin, Alan, C., Borghetti, Brett J., Peterson, Gilbert, L., “Predicting Trouble Ticket Resolution”, Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, Melbourne, FL, 21-23 May 2018.
    https://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS18/paper/download/17678/16882
  7. Vieane, Alex, Funke, Gregory, Greenlee, Eric, Mancuso, Vincent, Borghetti, Brett J., Miller, Brent, Menke, Lauren, Brown, Rebecca, Foroughi, Cyrus, K., and Boehm-Davis, Deborah, “Task Interruptions Undermine Cyber Defense”, Proceedings of the 2017 Human Factors and Ergonomics Society International Conference, Austin, TX, 9-13 October 2017 (Mark Resnick Best Paper Award Winner)
    https://www.researchgate.net/publication/320093832_Task_Interruptions_Undermine_Cyber_Defense
  8. Mash, R.L.*, Borghetti, B.J., Pecarina, J.M., “Improved Aircraft Recognition for Aerial Refueling through Data Augmentation in Convolutional Neural Networks ”, Proceedings of the 12th International Symposium on Visual Computing (ISVC’16), December 12-14, 2016, Las Vegas, Nevada, USA
  9. Hefron, R.G.*, Borghetti, B.J. “A New Feature for Cross-day Psychophysiological Workload Estimation, ” 15th IEEE International Conference on Machine Learning and Applications (ICMLA’16), December 18-20, 2016, Anaheim, California, USA
  10. Borghetti, B.J., Giametta, J.J.*, and Rusnock, C.F., “Estimating Continuous Operator Workload From Small Subject Samples”, Proceedings of the 2016 Human Factors and Ergonomics Society International Conference, Washington DC, 19-23 Sep 2016.
  11. Vieane, A., Funke, G., Mancuso, V., Greenlee, E., Dye, G.*, Borghetti, B.J., Miller, B., Menke, L., and Brown, R., “Coordinated Displays to Assist Cyber Defenders”, Proceedings of the 2016 Human Factors and Ergonomics Society International Conference, Washington DC, 19-23 Sep 2016  (Mark Resnick Best Paper Award Winner)
    https://journals.sagepub.com/doi/pdf/10.1177/1541931213601078
  12. Giametta, J.J.*, and Borghetti, B.J., “EEG-based Secondary Task Detection in a Multiple Objective Operational Environment”,  Proceedings of the 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), Miami, FL, 9-11 Dec 2015, pp 608-613.
  13. Smith, A.M.*, Borghetti, B.J., and Rusnock, C.F., “Improving Model Cross-Applicability for Operator Workload Estimation”, Proceedings of the 2015 Human Factors and Ergonomics Society International Conference, Los Angeles, CA, 26-30 Oct 2015, vol. 59, pp 681-685.
  14. Boeke, D.K*., Miller, M.E., Rusnock, C.F., Borghetti, B.J., “Exploring Individualized Objective Workload Prediction with Feedback for Adaptive Automation”  Proceedings of the 2015 Institute of Industrial Engineers(IIE)Industrial & Systems Engineering Research Conference, (ISERC) , Nashville, TN, 30 May-2 Jun, 2015., pp. 1437-1446.
  15. Shirey, R.G.*, Hopkinson, K.M., Stewart, K.E.*, Hodson, D.D. and Borghetti, B.J., “Analysis of Implementations to Secure Git for Use as an Encrypted Distributed Version Control System”, 48th IEEE Hawaii International Conference on System Sciences, 2015, pp 1530-1605.  http://conferences.computer.org/hicss/2015/papers/7367f310.pdf
  16. Kwak, H., Borghetti, B.J., “Reducing Communication Detection and Eavesdropping using Mobile Agent Relay Networks”, Proceedings of the Winter Simulation Conference (WSC) 2010, 5-8 December, 2010, pp 2832-2841
  17. *Weissgerber, K., Borghetti, B.J., Peterson, G.L., “An Effective and Efficient Real Time Strategy Agent,” Florida Artificial Intelligence Research Society Conference (May 2010).
  18. Thomas R.W., Komali, R.S., Borghetti, B.J., Mahonen, P., “A Bayesian Game Analysis of Emulation Attacks in Dynamic Spectrum Access Networks” IEEE Dynamic Spectrum Access Networks (DySPAN) (April, 2010)
  19. *Hooper, D.J., Peterson, G.L., Borghetti, B.J., “Dynamic Coalition Formation Under Uncertainty”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009), October 2009, St. Louis, MO.
  20. *Weissgerber, K., Borghetti, B.J., Lamont, G.B, Mendenhall, M., “Towards Automated Feature Selection in Real-Time Strategy Games,”  GAMEON-North America-09 (August 2009), [best paper award winner].
  21. *Borghetti, B.J., and Gini, M., “Weighted Prediction Divergence for Metareasoning”:  Association for the Advancement of Artificial Intelligence (AAAI2008) Workshop on Metareasoning, Chicago, IL, July 2008
  22. *Borghetti, B.J., Sodomka, E., Collins, J. and Gini, M., “A Market-Pressure-Based Performance Evaluator for TAC-SCM”:  Trading Agent Design and Analysis & Agent Mediated Electronic Commerce VIII Joint workshop at Autonomous Agents and Multi-Agent Systems Conference (AAMAS), Hakodate, Japan, May, 2006
  23. *Borghetti, B.J.,  Williams, E., Santos, E. Jr., “Inferencing Over Incomplete Solution Spaces with Genetic Algorithms for Probabilistic Reasoning”: Midwest Artificial Intelligence and Cognitive Science Conference  February 1996

Conference Publications (Refereed Abstract)

  1. *Brunson, Anthony C., Ryan D., Dill, Richard, Borghetti, Brett J., and Hodson, Douglas D., “Drone Range Detection Using Extracted Mel Frequency Cepstral Coefficients with Logistic Regression and Support Vector Machines”, IEEE International Conference on Scientific Computing (CSC’23) 2023, 24-27 Jul 2023, Las Vegas USA. (Accepted 4 Jun 2023)
  2. *Clendening, Ryan D., Dill, Richard, Borghetti, Brett J., Smolenski, Brett, Haddad, Darren, and Hodson, Douglas D., “Cellphone-based sUAS Range Estimation:  A Deep-Learning Approach”, World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'23), July 24 July 24-27, 2023; Las Vegas. (paper ID ICA2518, Accepted 18 May 2023)
  3. *Burt, Braden, Borghetti, Brett J., Franz, Anthony L., Holland, Darren E., and Bickley, Abigail A., “Application of Machine Learning Techniques to Magnetic Field Sensor Data Collected at HFIR” Poster Presentation, Conference on Data Analysis (CoDA) poster presentation 7-9 Mar 2023, Santa Fe, NM  )
  4. *Dicks, Preston J., Borghetti, Brett J., Franz, Anthony L., Holland, Darren E., and Bickley, Abigail A., “Transfer Learning Demonstration using Machine Learning Techniques with Multiphenomenological Data to Verify a Nuclear Reactor’s Operational State” Poster Presentation, Conference on Data Analysis (CoDA) poster presentation 7-9 Mar 2023, Santa Fe, NM
  5. *Brinker, Marcus W., Bickley, Abigail A., Borghetti, Brett J., Goldblum, Bethany F., Whetzel, Jonathan H., and Bevins, James E., “Machine Learning-Based Characterization of Nuclear Fuel Cycle Operations”, IEEE Symposium on Radiation Measurements and Applications (SORMA) West, 27 May 2021
  6. *Crow, David R., Graham, Scott R., Borghetti, Brett J., “Fingerprinting Vehicles with CAN Bus Data Samples”, 15th International Conference on Cyber Warfare and Security (ICCWS), Norfolk, VA, Feb 2020
  7. *Westing, Nicholas M., Borghetti, Brett J., Gross, Kevin C., “Analysis of Long-Wave Infrared Hyperspectral Classification Performance Across Changing Scene Illumination”, SPIE Defense and Commercial Sensing Baltimore, MD, 14-18 April, 2019.
  8. *Anthony, Keith D., Borghetti, Brett J., Steward, Brian J., “Initial Investigation into the Effect of Image Degradation on the Performance of a 3-Category Classifier Using Transfer Learning and Data Augmentation”, SPIE Defense and Commercial Sensing Baltimore, MD, 14-18 April, 2019.
  9. *Berhold, J. Mark, Leishman, Robert C., Borghetti, Brett J., Venable, Donald T., Hyperparameter Comparison on Convolutional Neural Network for Visual Aerial Localization, Institute of Navigation (ION) Pacific Position Navigation Timing (PNT) conference, Honolulu, HI, 8-11 April 2019.
  10. *McQuaid, Ian, Merkle, Laurence D., Borghetti, Brett J., Cobb, Richard, Fletcher, Justin “Space Object Identification Using Deep Neural Networks” Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS), 11-14 September 2018, Maui, HI  https://amostech.com/TechnicalPapers/2018/Astrodynamics/McQuaid.pdf
  11. *Jackson, Bryan V., Miller, Michael E., Borghetti, Brett, J., “Invoking Steady-State Visual Potentials Through Near Infrared Signals”, Institute of Industrial and Systems Engineers (IISE) Industrial Systems Engineering Research Conference (ISERC) 2018.
  12. Funke, G., Dye, G.*, Borghetti, B.J., Mancuso, V., Greenlee, E., Miller, B., Menke, L., Brown, R., and Vieane, A., “Development and Validation of the Air Force Cyber Intruder Alert Testbed (CIAT)”, 7th International Conference on Applied Human Factors and Ergonomics (AHFE), Orlando, FL, 27-31 July 2016
  13. Borghetti, B.J., and Rusnock, C.F., “Introduction to Real-Time State Assessment”, 18th International Conference on Human-Computer Interaction (HCII), Toronto, Canada, 17-21 July 2016)
  14. Rusnock, C.F., Borghetti, B.J., and McQuaid, I.W**., “Objective-Analytical Measures of Workload – the Third Pillar of Workload Triangulation”  9th International conference on Augmented Cognition, 17th international Conference on Human-Computer Interaction Los Angeles, CA, 2-7 Aug 2015.  LLNCS vol 9183, pp. 124-135.
  15. Sullivan, N.M.*, Borghetti, B.J., and Coutu, R.A., “Energy Harvesting & Recapture from Human Subjects: Dual-Stage Thermal MEMS Energy Converter”, IEEE Conference on Reliability Science for Advanced Materials and Devices (RSAMD), Golden, CO, 7?9 Sep, 2014
  16. *Borghetti, B.J., *Sodomka, E., “Performance Evaluation Methods for the Trading Agent Competition”  Student abstract and poster program at Association for the Advancement of Artificial Intelligence (AAAI), July, 2006.

Other Publications

  1. Borghetti, Brett J., Bickley, Abigail A., Noel, George E., Hill, Raymond R., and Schubert Kabban, Christine M., “Artificial Intelligence: Automating Data Analysis Decision-Making (Machine Learning Improves Many Air Force Missions)” AFIT ENgineer newsletter, special edition on Artificial Intelligence, Vol 2, Issue 4, Dec 2020.   https://www.afit.edu/EN/doclib.cfm?dl=135; https://www.afit.edu/docs/AFIT%20Engineer%20Dec2020_WEB.pdf

  2. *Borghetti, B.J., “Inference Algorithm Performance and Selection Under Constrained Resources,” Master’s Thesis: December 1996

  3. *Borghetti, B.J., “Opponent Modeling in Interesting Adversarial Environments,”  Doctoral Dissertation, Aug 2008

  4. Thomas, R. W, Borghetti, B.J., “IA Implications for Software Defined Radio, Cognitive Radio and Networks”, IA Newsletter, Information Assurance Technical Analysis Center, Vol. 12, No. 1, Spring 2009, pp. 20-24.

Invention Disclosures

  1. Miller, Michael, E, Borghetti, Brett, J., Stephens, Chad, Kennedy, Kellie,  “Display System Interface Using Visually-Evoked Cortical Potentials (VECP)”, 25 April 201

Invited Talks and Presentations 

  1. Le Blanc, Katya, Pinelis, Jane, and Borghetti, Brett J., “Mathematics for Artificial Reasoning in Science (MARS) Human Factors Panel Discussion”, Invited panelist for Pacific Northwest National Laboratory (PNNL), 24 May 2022
  2. Borghetti, Brett J., “Machine Learning, A gentle Introduction”, Invited speaker for Cybersecurity and Intelligence Working Group (AFLCMC 21IS AF-CROWS CSIWG), 12 Jan 2022
  3. Lau, Nathan, Boyle, Linda, Borghetti, Brett.J., Friedman, Lex, Barnes, Laura, Hildebrandt, Michael, Lee, John D., Panel Discussion:  “Machine Learning and Human Factors:  Status, Applications & Future Directions”, Invited Panel at Human Factors and Ergonomics Society Annual Conference, Philadelphia, PA 1-5 Oct 2018.
    https://doi.org/10.1177%2F1541931218621031
  4. Borghetti, Brett. J., Funke, Gregory, Pastel, Robert, and Gutzwiller, Robert., Panel Discussion:  Cyber Human Research from the Cyber Operator’s View.  Invited Panel at Human Factors and Ergonomics Society Annual Conference, Austin, TX,  9-13 Oct, 2017 https://doi.org/10.1177%2F1541931213601569  
  5. Borghetti, B.J., et al. Panel discussion on Teaching Excellence (6 faculty members).  AFIT/EN Faculty Development Monthly Seminar, 30 Aug 2017 
  6. Borghetti, B.J., Machine Learning, a Gentle Introduction.  Association of Computing Machinery (ACM) colloquium, Cedarville University, Cedarville, OH,  21 March 2017
  7. Rusnock, C.F., Borghetti, B.J., “Assessing Mental Workload by Combining Model-based and Psychophysiological Measurement Approaches”  Institute of Industrial Engineers (IIE) Industrial Systems Engineering Research Conference (ISERC)May 21-24, 2016
  8. Rusnock, C.F., Borghetti, B.J., and McQuaid, I.W., “Predicting Operator Workload Using a Combined Modeling Approach”  AFIT-AFRL Colloquium - Human Machine Systems 2.0, 30 Sep 2014
  9. Miller, M.E., Peterson, G.L., Rusnock, C.F., and Borghetti, B.J., “AFIT Adaptive Automation Research Portfolio,” Ahead Autonomy Research Showcase 10 December 2013, Dayton, OH.
  10. Borghetti, B.J. “Anomaly Detection Through Behavior Signatures”, Invited Presentation, 3rd International Symposium on Resilient Control Systems, Idaho Falls, ID, Aug 2010

* Denotes student, ** Denotes Research Assistant

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