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Dr. Torrey Wagner, Assistant Professor of Data Analytics

Data Analytics Graduate Certificate Faculty

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DSN: 785-3636
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Dr. Torrey Wagner is an Assistant Professor of Data Analytics supporting the AFIT/EN Data Analytics graduate certificate program.

Dr. Wagner's current research interests are the application of machine learning and artificial intelligence techniques to improve the efficiency and performance of DoD organizations. He developed the python-based DASC 522 Machine Learning and SATI 532 Data Visualization & Communication courses, and their descriptions are shown below. Dr. Wagner also teaches the DASC 511 Object-Oriented Programming using Python course.

DASC 522 Machine Learning:  This course prepares students to apply machine learning methods to solve military problems using the Python environment. Supervised and unsupervised learning techniques including classification, regression and clustering will be covered, along with an overview of reinforcement learning techniques. After reviewing classical machine learning methods, the course will focus on the structure and application of neural networks. Students will modify python scripts and apply them to several types of data analytics problems. These techniques will give students the ability to answer questions from data, including inference, estimation, and prediction. This course will use the CRISP-DM process with a focus on understanding & preparing data, selecting a modeling approach, model building, performance assessment and both evaluating and interpreting model results.

SATI 532 Data Visualization & Communication: This course examines how data and information visualization can enhance both the rigorous analytic thinking needed to better understand threats and to effectively present the resulting analytic findings to decision makers.  This course covers both visual analytics and visualization.  It starts with the basics of how people perceive and think about the external world, based on current scientific findings.  This provides context as to what constitutes sound visual design principles.  An understanding of these is leveraged to create useful and compelling infographics.  Study of these basics of visualization provides foundational knowledge for application to visual analytics and analytic inquiry.  Key aspects of these topics include proper data and information selection and sampling; integration of structured as well as unstructured data; and the generation of multiple alternative hypotheses to explain what has been observed as well as the related predictions.  Class lectures and exercises will illustrate how sound visual design principles and effective infographics can be used to support reasoning relative to data selection and sampling, hypothesis generation, consideration of alternatives, and evaluation of predictions. 

DASC 511 Object-Oriented Programming Using Python:  This course prepares students to design solutions to data analytics problems using Python-based Object-Oriented Programming (OOP) techniques. Basic concepts of programming are reviewed, including flow control methods, functions, types and classes. Then, the role of abstractions, encapsulation, inheritance, and polymorphism are examined, with a focus on the data to be analyzed. Additional topics include data import, data structures, an overview of OOP design patterns and the selection of an appropriate pattern.

Education

  • PhD, Air Force Institute of Technology, 2010, Electrical Engineering with an Electro-optics focus
  • MS, Loughborough University (UK), 2004, Aerospace Systems Engineering
  • BS, University of Minnesota, 2000, Electrical Engineering

Publications

Peer-Reviewed Journal Publications (25)

  1. P. Reeser*, T. Wagner, J. Ritschel, M. Brown, B. Langhals, “Predicting Production Aircraft Engine Unit Cost Using Statistical Methods and Machine Learning” Journal of Defense Research & Engineering, Vol. 8, No. 2 (2025)
  2. R. Everman*, T. Wagner, N. Ranly, B. Cox, “Aircraft Detection from Satellite Imagery Using Synthetic Data,” Journal of Defense Modeling & Simulation (2025), Link
  3. C. Woodrum, T. Wagner, D. Weeks, “Improving 2-5 Qubit Quantum Phase Estimation Circuits Using Machine Learning,” Algorithms, Vol 17, No. 5 (2024) Link
  4. T. Wagner, D. Guhl*, B. Langhals, “The Impact of Data Preparation and Model Complexity on the Natural Language Classification of Chinese News Headlines,” Algorithms, Vol 17, No. 132 (2024) Link
  5. B. Meyer*, T. Wagner, B. Langhals, “Machine Learning Prediction of Alaskan F-22 Sortie Cancellations Based on Weather,” Journal of Defense Research & Engineering, Vol 6, No. 5 (2023)
  6. J. Turner, T. Wagner, B. Langhals, "Biomechanical & Psychologic Predictors of Failure in the Air Force Physical Fitness Test." Sports, Vol. 10, No. 4 (2022). Link
  7. L. Zoboroski*, T. Wagner, B. Langhals, “Classical and Neural Network Machine Learning to Determine the Risk of Marijuana Use.” International Journal of Environmental Research and Public Health.  Vol. 18 (2021) Link
  8.  C. Christensen*, T. Wagner, B. Langhals “Year-Independent Prediction of Food Insecurity Using Classical & Neural Network Machine Learning Methods,” AI, Vol. 2 (2021) Link
  9. C. Beal, A. Cuellar, T. Wagner "Sustainability Assessment of Alternative Jet Fuel for the U.S. Department of Defense," Biomass and Bioenergy, Vol. 144 (2021) Link
  10. J. Pearson*, T. Wagner, J. Delorit and S. Schuldt, "Cost Analysis of Optimized Islanded Energy Systems in a Dispersed Air Base Conflict," Energies, Vol. 13, No. 18 (2020) Link
  11. J. Pearson*, T. Wagner, S. Schuldt, "Meeting Temporary Facility Energy Demand With Climate-Optimized Off-Grid Energy Systems," IEEE Open Access Journal of Power & Energy, Vol. 7 (2020) Link
  12. R. Maglinao, T. Wagner, K. Duff, "Effects of Temperature and Antioxidants on the Oxidation of Biodiesel Derived from Waste Vegetable Oil," Journal of the American Oil Chemists Society, Vol. 97, No. 9 (2020), Link
  13. D. Martin-Abood*, D. Dudis, T. Wagner, "Solar Photovoltaic Considerations for Operational and Warfighter Support Capabilities," Journal of the Homeland Defense and Security Information Analysis Center, Vol. 7, No. 1 (2020) Link
  14. C. Pasion*, T. Wagner, C. Koschnick, S. Schuldt, J. Williams, K. Hallinan, "Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data," Energies, Vol. 13 No. 10 (2020) Link. Selected as volume cover.
  15. K. Flenar*, T. Wagner, A. Cox, D. Jacques, "Determining Detectable and Exploitable Aspects of Rogue Unmanned Aircraft Systems," Journal of Defense Research & Engineering, Vol. 3, No. 1 (2020)
  16. J. Kramer*, T. Wagner, “Developmental Test and Requirements Best Practices of Successful Information Systems Efforts using Agile Methods,” Defense Acquisition Research Journal, Vol. 26, No. 2 (2019)
  17. T. McWhirter*, T. Wagner, D. Rizzo, J. Stubbs, J. Williams, “Tracked Vehicle Physics-Based Energy Modelling and Series Hybrid System Optimization for the Bradley Fighting Vehicle,” Int’l Journal of Electric & Hybrid Vehicles, Vol 12, No. 1
  18. N. Thomsen*, T. Wagner, A. Hoisington, S. Schuldt, “A Sustainable Prototype for Renewable Energy: Optimized Prime-Power Generator Solar Array Replacement,” International Journal of Energy Production and Management, Vol. 4, No. 1 (2019)
  19. P. Hines*, T. Wagner, C. Koschnick, S. Schuldt, “Analyzing the Efficiency of Horizontal Photovoltaic Cells in Various Climate Regions,” Journal of Energy and Natural Resources, Vol. 8, No. 2 (2019)
  20. B. Bailey*, T. Wagner, J. Williams, “E700XD Portable Doppler Radar Energy Systems Analysis,” International Journal of Electrical Energy, Vol. 7, No. 2, doi: 10.18178/ijoee.7.2.62-66 (2019)
  21. P. Ramsey*, D. Prigge V, T. Wagner, A. Thal, “Statistical Viability Analysis of United States Air Force Estimating Cost Factor for Sustainable Construction,” Journal of Advances in Civil Engineering, Vol. 5, No. 2 (2019)
  22. D. Chester*, T. Wagner, D. Dudis,  “36% Reduction in Fuel Resupply Using a Hybrid Generator & Battery System for an Austere Location,” Marine Corps Gazette – The Professional Journal of the United States Marine Corps, Vol. 103, No. 3 (2019)
  23. J. Poole*, T. Wagner, D. Dudis, “8x Raven Small UAS Endurance with an Optimized Hybrid Solid Oxide Fuel Cell & Battery Energy System,” Journal of Defense Research & Engineering, Vol. 1, No. 2 (2018)
  24. T. Wagner, T. Ford, “DoD Applications of Agile Software Systems Engineering Methods”, Journal of Defense Research & Engineering, Vol. 1, No. 3 (2018)
  25. T. Wagner, M. Bohn, R. Coutu, L. Gonzalez, J. Murray, K. Schepler, and S. Guha, "Measurement and modeling of infrared nonlinear absorption coefficients and laser-induced damage thresholds in Ge and GaSb," J. Opt. Soc. Am. B, Vol. 27, No. 10 (2010)

 

Peer-Reviewed Conferences (22 based on paper review, 7 based on abstract review)

paper reviewed

  1. E. Tyndall^#, C. Gayheart*, A. Some*, J. Genz, B. Langhals, T. Wagner, “Undergraduate Pacific Studies Exam Generation and Answering Using Retrieval Augmented Generation and Large Language Models,” Hawaii International Conference on System Sciences, Kailua-Kona, HI, January 2025
  2. J. Smith*, E. Mbonimpa#, T. Wagner, B. Langhals, “Predictive Analysis of Defense Language Proficiency Test Outcomes: A Comparative Study Using Neural Networks and Logistic Regression,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, July 2024
  3. R. Peterson*#, T. Wagner, P. Auclair, B. Langhals, “Multi-class Classification of Satellite Orbits for Database Quality Control,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, July 2024
  4. J. Saul*, T. Wagner#, E. Mbonimpa, B. Langhals, “Atmospheric Meteorological Effects on Forecasting Daily Lightning Occurence at Cape Canaveral Space Force Station,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, 2023
  5. T.Tucker*#, T. Wagner, P. Auclair, B. Langhals, “Machine Learning Prediction of DoD Personal Property Shipment Costs,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, 2023
  6. G. Yuchi*, T. Wagner, P. Auclair, B. Langhals#, “Effect of Connection State & Transport/Application Protocol on the Machine Learning Outlier Detection of Network Intrusions,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, 2022
  7. L. Turner*, T. Wagner, P. Auclair, B. Langhals#, “Machine Learning Land Cover and Land Use Classification of 4-band Satellite Imagery,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, 2022
  8. A. Fenoglio*#, T. Wagner, P. Auclair, B. Langhals, “Effect of Trigonometric Transformations on the Machine Learning Prediction and Quality Control of Air Temperature,” World Congress in Computer Science, Computer Engineering, and Applied Computing, Las Vegas, NV, 2022
  9. C. Szul*#, T. Wagner, B. Langhals, "Synthetic Aperture Radar Image Recognition of Armored Vehicles," 89th Military Operations Research Society Symposium, Virtual, Jun 2021.
  10. S. E. Carrasco*#, T. Wagner, B. Langhals, "Per-pixel Cloud Cover Classification of Multispectral Landsat-8 Data," 89th Military Operations Research Society Symposium, Virtual, Jun 2021.
  11. R. Larkin*#, T. Wagner, B. Mullins, “Securing Photovoltaic (PV) System Deployments with Data Diodes,” 47th IEEE Photovoltaic Specialists Conference, Virtual, Jun 2020.
  12. N. Thomsen*#, D. Papazoglou, T. Wagner, A. Hoisington, S. Schuldt, “A Multi-Criteria Logistics Analysis of Photovoltaic Modules for Remote Applications,” 47th IEEE Photovoltaic Specialists Conference, Virtual, Jun 2020.
  13. T. Wagner#, T. Ford, “'Metrics to Meet Security & Privacy Requirements with Agile Software Development Methods in a Regulated Environment,” IEEE Conference on Computing, Networking and Communications, Kailua-Kona, HI, Feb 2020.
  14. J. Pearson*#, T. Wagner, S. Schuldt, “Insulation Sensitivity Analysis for an Optimized Fabric Shelter Off-grid Hybrid Energy System,” 15th Dayton Engineering Sciences Symposium, Dayton, OH, USA, 29 Oct 2019.
  15. N. Thomsen*#, T. Wagner, A. Hoisington, R. Salavani, S. Schuldt, “A Sustainable Prototype for Renewable Energy,” Air Force Institute of Technology Centennial Celebration, Dayton, OH, USA, Nov 2019.
  16. J. Kramer*#, T. Wagner, “Developmental Test and Requirements Best Practices of Successful Information Systems Efforts using Agile Methods,” Defense Acquisition University Symposium, Fort Belvoir, VA, April 2019.
  17. N. Thomsen*#, T. Wagner, A. Hoisington, S. Schuldt, “A Sustainable Prototype for Renewable Energy: Optimized Prime-Power Generator Solar Array Replacement,” 8th International Conference on Energy and Sustainability, Coimbra, Portugal, Jul 2019.
  18. T. McWhirter*#, T. Wagner, “Ground Vehicle Energy Requirement Modeling and System Optimization,” Society of Automotive Engineers World Conference, Detroit, MI, April 2019.
  19. T. Wagner#, E. Lang, W. Assink and D. Dudis, "Photovoltaic System Optimization for an Austere Location Using Time Series Data," 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC), Waikoloa Village, HI, 2018, pp. 1239-1243; doi: 10.1109/PVSC.2018.8548145.
  20.  (invited paper) T. Wagner#, "Fiber laser beam combining and power scaling progress: Air Force Research Laboratory Laser Division", Photonics West, Proc. SPIE 8237, Fiber Lasers IX: Technology, Systems, and Applications, 823718; doi:  10.1117/12.912154 (2012).
  21. T. Wagner#, M. Bohn, R. Coutu, Jr., L. Gonzalez, J. Murray, K. Schepler and S. Guha, "Mid-IR Nonlinear Absorption and Damage Study in Ge and GaSb,” Directed Energy Professional Society 24th Annual Solid State and Diode Laser Technology Review, Santa Fe, New Mexico, 6-10 June 2011.
  22. V. Fedorov#, I. Moskalev, M. Mirov, S. Mirov, T. Wagner, M. Bohn, P. Berry, K. Schepler, “Energy scaling of nanosecond gain-switched Cr2+:ZnSe lasers,” Proceedings of the SPIE 7912, San Francisco, California, Paper 7912-51, 22-27 January 2011.

abstract reviewed

  1. B. Martin^#, D. Hodson, M. Grimaila, T. Wagner, “Predictive Implications of Space Weather on Quantum Network Functionality”, HamSCI Workshop, New Jersey Institute of Technology, March 2025
  2. B. Martin^#, D. Hodson, M. Grimaila, T. Wagner, W. McKenzie, A. Richards, “Predicting White Rabbit Time Synchronization Error on DC-QNet Using Statistical Machine Learning Methods,” Institute of Navigation Precise Time and Time Interval Meeting, January 2025
  3. C. Woodrum#, T. Wagner, D. Weeks, “Improving Phase Estimation by Post Processing QPE Circuit Output” American Physical Society March Meeting, Minneapolis MN, March 2024 Link.
  4. N. Thomsen*#, S. Schuldt, T. Wagner, A. Hoisington, R. Salavani, S. Risser, “Sustaining Contingency Bases Through Solar Power,” Society of American Military Engineers Professional Development Webinar, 16 Sep 2020 Link.
  5. N. Thomsen*#, T. Wagner, A. Hoisington, R. Salavani, S. Schuldt, “A Sustainable Prototype for Renewable Energy,” Air Force Institute of Technology Centennial Celebration, Dayton, OH, USA, Nov 2019.
  6. N. Thomsen*#, T. Wagner, A. Hoisington, S. Schuldt, “A Sustainable Prototype for Renewable Energy: Optimized Prime-Power Generator Solar Array Replacement,” 15th Dayton Engineering Sciences Symposium, 29 Oct 2019.
  7. J. Pearson*#, T. Wagner, S. Schuldt, “Insulation Sensitivity Analysis for an Optimized Fabric Shelter Off-grid Hybrid Energy System,” 15th Dayton Engineering Sciences Symposium, Dayton, OH, USA, 29 Oct 2019.

 

Book Chapters (2)

  1. T. Wagner, “Augmenting a Curriculum Review with Generative AI”, Chapter 18, pages 222-231, in AFIT Generative AI Teaching Guidebook. Wright-Patterson AFB: Air Force Institute of Technology, (2025).   Link
  2. M. Bateman, B. Borghetti, A. Dukes, N. Francis, M. Frick, B. Oh, K. Patterson, H. Patel, M. Reith, E. Tyndall, T. Walton, T. Wagner, T. Wolfe, and J. Zemmer, “AFIT Generative AI Teaching Guidebook Synopsis” Chapter 1, pages 1-12, in AFIT Generative AI Teaching Guidebook. Wright-Patterson AFB: Air Force Institute of Technology, (2025).   Link

 

Other Publications and Presentations (14)

  1. N. Ranly, T. Wagner, “Rapid Experimentation with Python Considering Optional and Hierarchical Inputs,” arXiv, 2025 (Link)
  2. B. Langhals, T. Wagner, “Enabling Decision Advantage with AFIT's Data Analytics Certificate Program,” AFIT Engineer Newsletter, pp 14-15, Vol. 6, Issue 4, 2024 (Link)
  3. T. Wagner, K. Binsted, N. Ranly, W. Wu, “Augmenting Data Analytics Using Natural Language Processing and Large Language Models,” Hawai?i International Conference on System Sciences, Kailua-Kona, HI, January 2025. (this is a summary of the minitrack, created in my role as minitrack chair)
  4. T. Wagner, D. Guhl, B. Langhals, “Using Data Analytics to Perform a Task in a Foreign Language using Multiple Algorithms,” AFIT/CIE Lunch & Learn, June 2024
  5. J. Turner, T. Wagner, B. Langhals, “Dataset: Biomechanical & Psychological Predictors of Failure in the Air Force Physical Fitness Test,”  Mendeley Data; Mendeley Ltd., London, UK, http://dx.doi.org/10.17632/tnc4k48bbj.1, (2022)
  6. J. Williams, T. Wagner, “Northern Hemisphere Horizontal Photovoltaic Power Output Data for 12 Sites”, Mendeley Data, http://dx.doi.org/10.17632/hfhwmn8w24.5 (2020)
  7. T. Wagner#, “Optimization of Airspeeds and Altitudes for F-15E and KC-135 Coronet Missions,” Deputy Assistant Secretary of the Air Force for Operational Energy, Washington D.C., 10 Jun 2019.
  8. T. Wagner#, “Optimization of Airspeeds and Altitudes for Coronet Missions,” Air Force Research Laboratory Aerospace Vehicles Directorate, Dayton OH, 18 Jun 2019.
  9. T. McWhirter*, T. Wagner, “30-66% Reduction in Fuel Consumption Using AFRL Flight line Hybrid Electric Generators at Marine Corps Expeditionary Advanced Bases”, USMC 2nd Quarter FY19 Innovation Challenge proposal (2019)
  10. K. Meyer*#, T. Wagner, J. Williams, “Using Wind and Hydro Power to Sustain the Off-Grid Power Supply for a 50’ Cruising Sailboat,” Journal of Fundamentals of Renewable Energy and Applications, Vol. 9, No. 1 (2019)
  11. L. Cowen*, T. Wagner, D. Dudis, J. Williams# “Austere Location Wind Turbine Energy System Analysis,” Journal of Fundamentals of Renewable Energy and Applications, Vol 9, No. 2 (2019).
  12. G. Moore, T. Wagner, “AFRL/RDLA Modeling and Simulation Work,” Air Force Research Laboratory Technical Paper AFRL-RD-PS-TP-2011-0003 (2011)
  13. T. Wagner, “All Solid-State Mid-IR Laser Development, Nonlinear Absorption Investigation and Laser-Induced Damage Study”, Dissertation, Air Force Institute of Technology (2010)
  14. T. Wagner, “Radio Frequency, Systems and Tactics Modeling of a Large Aircraft Air-to-Air Missile Engagement”, Thesis, Loughborough University UK (2004)
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