Trevor Joseph Bihl, PhD

Department:
Biomed Indust & Human Factor Engr
Title:
Adjunct Assistant Professor, Pharmacology & Toxicology; Adjunct Faculty, Biomedical, Industrial & Human Factor Eng.
Address:
Russ Engineering Center 207, 3640 Colonel Glenn Hwy, Dayton, OH 45435-0001
Education History: 

PhD in Electrical Engineering (2015), Air Force Institute of Technology (Wright Patterson AFB, OH)

MS in Electrical Engineering (2011), Ohio University (Athens, OH)

BS in Electrical Engineering (2005), Ohio University (Athens, OH)

 

Academics

Research statement: 

My research encompasses the areas of electrical engineering, applied statistics and operations research. I am also heavily involved in sponsor interaction and grant writing.  I primarily focus on methods for:

  1. Artificial Intelligence and Cognitive Systems
  2. Machine Learning and Data Mining
  3. Cyber and cyber-physical systems
  4. Biostatistics and Medical Data Analysis
  5. Signal Processing
  6. Sensor Data Exploitation: Remote Sensing, Cyber
  7. Control Systems and Signal Processing
  8. Data Visualization
  9. "Big Data"
  10. Business Analytics
  11. Automation
  12. Combat Identification

In these areas, my focus is largely in real world application, e.g. where reality and technology intersect.  Due to this, while I investigate novel methods, I avoid novelty for novelty's sake.  I believe all data is a matrix in the end and see much to be gained in the broad interconnection of domains/disciplines. Thus many methods I've developed or collaborate on might extend applied statistics, but to a physics-based problem.

 

Service: 

Associate Editor:

Active Peer Reviewer (averaging 30+ reviews a year) for:

  • American Controls Conference
  • Artificial Neural Networks in Engineering Conference                                                              
  • Digital Signal Processing                                                                                                             
  • IEEE Geoscience and Remote Sensing Letters
  • IEEE Signal Processing Letters
  • IEEE Transactions on Control Systems Technology
  • IEEE Transactions on Information Forensics and Security                                                       
  • IEEE Transactions on Image Processing
  • IEEE/ASME Transactions on Mechatronics                                                                               
  • IEEE Transactions on Power Delivery
  • IEEE Transactions on Sensor Networks
  • IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
  • IFAC Symposium on Automatic Control in Aerospace                                                               
  • Information Fusion
  • International Journal of Business Analytics
  • International Journal of Electrical Engineering Education
  • Journal of Algorithms and Computational Technology
  • Mathematical Problems in Engineering
  • Military Operations Research Journal                                                                                        
  • Optical Engineering
  • Remote Sensing
Students Advised: 

Thesis Committee Membership                                                                                       

 

Air Force Institute of Technology  MS in Operations Research                                                                                                          

  • Steven Chon, (Feb. 2019), Hyper-parameter Optimization of a Convolutional Neural Network, Chair: Dr. Daniel Steeneck
  • Robert Gutierrez, (Feb. 2017) A Tabulated Vector Approach for Log-based Anomaly Detection, Chair: Dr. Kenneth Bauer
  • Brendan McLean (Feb. 2016) Autoencoded Reduced Clusters for Anomaly Detection Enrichment (ARCADE) in Hyperspectral Imagery, Chair: Dr. Kenneth Bauer
  • Russell Walter (Feb. 2016) Methods to Address Extreme Class Imbalance in Machine Learning Based Network Intrusion Detection Systems, Chair:  Dr. Kenneth Bauer

 

Wright State University  MS in Industrial and Human Factors Engineering (MSIHE)                                                

  • Melissa Coral (May, 2016) Analyzing Cognitive Workload Through Eye-related Measurements: A Meta-Analysis, Chair: Dr. Mary Fendley

Professional

Publications: 

Peer Reviewed Journal Publications (*indicates student 1st author)

  1. Bihl, T. J., Paciencia, T. J., Bauer, K. W., and Temple, M. A., (2020) “Cyber-Physical Security with RF Fingerprint Classification through Distance Measure Extensions of Generalized Relevance Learning Vector Quantization,” Security and Communications Networks, in pres
  2. Paciencia, T. J.*, Bihl, T. J., and Bauer, K. W., (2019) “Improved n-dimensional data visualization from hyper-radial values,” Journal of Algorithms and Computational Technology, vol. 13
  3. Travers, J. B., Poon, C., Bihl, T. J., Borchers, C., Rohrbach, D. J., Borchers, S., Trevino, J., Rubin, M., Donnelly, H., Kellawan, K., Carpenter, L., Bahl, S., Rohan, C., Muennich, E., Guenthner, S., Hahn, H., Rkein, Al, Darst, M., Mousdicas, N., Cates, E., Sunar, U., (2019) “Quantifying skin photodamage with spatial frequency domain imaging: Statistical results,” Biomedical Optics Express, vol 10, no 9, pp. 4676-83
  4. Gutierrez, R. J.*, Bauer, K. W., Boehmke, B. C., Saie, C. M., and Bihl, T. J. (2018) "Cyber Anomaly Detection: Using Tabulated Vectors and Embedded Analytics for Efficient Data Mining" Journal of Algorithms and Computational Technology, vol. 12, no. 4 (2018): 293-310
  5. Butler, H. K.*, Friend, M. A., Bauer, K. W., Bihl, T. J., (2018) “The Effectiveness of Using Diversity to Select Multiple Classifier Systems With Varying Classification Thresholds,” Journal of Algorithms and Computational Technology,  vol. 12, no. 3, pp.187-199
  6. Gutierrez, R. J.*, Boehmke, B. C., Bauer, K. W., Saie, C. M., and Bihl, T. J. (2017) “anomalyDetection: Implementation of Augmented Network Log Anomaly Detection Procedures,” R Journal, August 2017
  7. Bihl, T. J., and Bauer, K. W., (2017) "Statistical Analysis of High-Level Features from State of the Union Addresses," International Journal of Information Systems and Social Change (IJISSC), vol. 8, no. 2, pp. 50-73
  8. Moore, K. L.*, Bihl, T. J., Bauer, K. W., and Dube, T. E., (2017) "Cyber Data Feature-Extraction and Artificial Neural Network Based Feature-Selection for Classifying Cyber-Traffic Threats," Journal of Defense Modeling and Simulation, vol. 13, no. 3, pp. 217-231
  9. Bihl, T. J., Bauer, K. W., and Temple, M. A., (2016) "Feature Selection for RF Fingerprinting with Multiple Discriminant Analysis and Using ZigBee Device Emissions," IEEE Transactions on Information Forensics and Security, vol. 11, no. 8, pp. 1862-1874
  10. Situ, J. X.*, Friend, M. A., Bauer, K. W., and Bihl, T. J., (2016) " Contextual Features and Bayesian Belief Networks for Improved Synthetic Aperture Radar Combat Identification," Military Operations Research Journal, vol. 21, no. 1, pp. 89-106
  11. Bihl, T. J., Young, W. A., and Weckman, G. R., (2016) "Defining, Understanding and Addressing Big Data," International Journal of Business Analytics (IJBAN), vol. 3, no. 2, pp. 1-32
  12. Jablonski, J. A.*, Bihl, T. J., Bauer, K. W., (2015) “Principal Component Reconstruction Error for Hyperspectral Anomaly Detection,” IEEE Transactions on Geoscience and Remote Sensing Letters, vol. 12, no. 8, pp. 1725-1729
  13. Friesen, K. D.*, Bihl, T. J., Bauer, K.W., and M. A. Friend, (2013) “Contextual Anomaly Detection Cueing Methods for Hyperspectral Target Recognition,” American Journal of Science and Engineering, vol. 2, no. 1,  pp. 9-16 
  14. Williams, J.*, Bihl, T. J., and Bauer, K., (2013) "Towards the mitigation of correlation effects in anomaly detection for hyperspectral imagery,” Journal of Defense Modeling and Simulation, vol. 10, no. 3, pp. 263-273 
  15. Ryer, D.M.*, Bihl, T. J., Bauer, K.W., and Rogers, S.K., (2012) “QUEST Hierarchy for Hyperspectral Face Recognition,” Advances in Artificial Intelligence, vol. 2012,  13 pages

Books

  1. Zobaa, A. and Bihl, T. J. (editors), Big Data Analytics in Future Power Systems, CRC Press, 2018
  2. Bihl, T. J., Biostatistics Using JMP: A Practical Guide, SAS Press, 2017

Book Chapters and Technical Reports

  1. Zobaa, A. and Bihl, T. J. (2018) “Introduction to Big Data in Power Systems,” Big Data Analytics in Future Power Systems, CRC Press, pp. 1-7
  2. Zobaa, A. and Bihl, T. J. (2018) “Communication Devices and Identity Verification Methods for Critical Infrastructure Applications,” Big Data Analytics in Future Power Systems, CRC Press, pp. 85-106
  3. Bihl, T. J. and Zobaa, A. (2018) “Data Mining Methods for Electricity Theft Detection,” Big Data Analytics in Future Power Systems, CRC Press, pp. 107-124
  4. Bihl, T. J., (2018) “Advanced Flywheel Technologies for Energy Storage,” A. F. Zobaa, P. F. Ribeiro, S. H. E. Abdel Aleem, & S. N. Afifi (Eds.), The Future Roles and Challenges of Energy Storage,  The Institute of Engineering Technology, pp. 239-260
  5. Bihl, T. J., Young, W. A., and Weckman, G. R., "Artificial Neural Networks and Applications in Business," Encylopedia of Information Science and Technology, 4th Edition, invited: May 2016
  6. Frey, J. S., Bihl, T. J., Kobayashi, A., Mitchell, S. W., Dillard, S. C., Mauzy, C. A., and Mattie, D. R., (2015) " Examination of Urinary B-Naptholas a biomarker Indicative of Jet Fuel Exposures, AFRL Technical Report
  7. Jacobsen, J. J., Polito, A. B., Chapleau, R. R., Maurer, E. I., Frey, J. S., Bihl, T. J., and Mauzy, C. A., (2014) “Interaction of Jet Fuel Hydrocarbon Components with Red Blood Cells and Hemoglobin,” AFRL Technical Report
  8. Bihl, T. J., Young, W. A., and G. R. Weckman, “Decision Support Systems in Business,” Encyclopedia of Business Analytics and Optimization, 1st Ed., vol. 2, 2014, pp. 144-158 
  9. Young, W. A., Bihl, T. J., and G. R. Weckman, “Artificial Neural Networks for Business: A Starting Point,” Encyclopedia of Business Analytics and Optimization, 1st Ed., vol. 1, 2014, pp. 200-215

Conference Proceedings  (*indicates student 1st author)

  1. Bihl, T. J., Gutierrez, R., Bauer, K. W., Boehmke, B. C., and Saie, C., (2020) “Topological Data Analysis for Enhancing Embedded  Analytics for Enterprise Cyber Log Analysis and Forensics,” Hawaii International Conference on System Sciences (HICSS), Maui, HI, pp. 1937 – 1946.  (<45% acceptance rate)
  2. Bihl, T. J., Jones, A., Schoenbeck, J., Steeneck, D. and Jordan, J., (2020) “Finding Algorithm Settings: Easy and Efficient Hyperparameter Optimization to Address Some Artificial Intelligence “ilities”,” Hawaii International Conference on System Sciences (HICSS), Maui, HI, pp. 943 – 952 (<45% acceptance rate)
  3. Bihl, T. J., and Talbert, M., (2020) “Analytics for Autonomous C4ISR within e-Government: a Research Agenda,” Hawaii International Conference on System Sciences (HICSS), pp. 2218 - 2227 (<45% acceptance rate)
  4. Berthold, B., Bihl, T. J., Cox, C., Jenkins, T.A., and Leland, L., (2019) “Probabilistic reasoning for real-time UAV decision and control,“ 2019 SPIE Defense and Commercial Sensing, Baltimore, MD
  5. Bihl, T. J., Jenkins, T., Cox, C., DeMange, A., Hill, K., and Zelnio, E., (2019) “From Lab to Internship and Back Again: Learning Autonomous Systems through Creating a Research and Development Ecosystem” Ninth Symposium on Educational Advances in Artificial Intelligence, Honolulu, HI, accepted
  6. Bihl, T. J., Cox, C. and Jenkins, T. (2018) “Finding Common Ground by Unifying Autonomy Indices to Understand Needed Capabilities,” 2018 SPIE Defense and Commercial Sensing, to appear
  7. Bihl, T. J. and Steeneck, D. W. (2018) “Multivariate Stochastic Approximation to Tune Neural Network Hyperparameters for Critical Infrastructure Communication Device Identification,” 2018 Hawaii International Conference on System Sciences (HICSS), pp. 2225-2234 (<45% acceptance rate)
  8. Bihl, T. J. and Hajjar, S. (2017) “Electricity Theft Concerns within Advanced Energy Technologies,” 2017 IEEE National Aerospace and Electronics Conference (NAECON),  Dayton, OH
  9. Steeneck, D. W. and Bihl, T. J., (2017) “Stochastic Approximation for Learning Rate Optimization for Generalized Relevance Learning Vector Quantization,” 2017 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH
  10. Bihl, T. J., Temple, M. A., Bauer, K.W., (2017) “An Optimization Framework for Generalized Relevance Learning Vector Quantization with Application to Z-Wave Device Fingerprinting,” 2017 Hawaii International Conference on System Sciences (HICSS), pp. 360 – 365  (<45% acceptance rate)
  11. Bihl, T. J., Temple, M. A., and Bauer, K. W. (2016), "Feature Selection Fusion (FSF) for Aggregating Relevance Ranking Information with Application to ZigBee Radio Frequency Device Identification," IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH
  12. Bihl, T. J., Temple, M. A., Bauer, K. W. and Ramsey, B., (2015) "Dimensional Reduction Analysis for Physical Layer Device Fingerprints with Applications to ZigBee and Z-Wave Devices," Military Communications Conference (MILCOM), Tampa, FL, pp. 360-365
  13. Carbino, T. J., Temple, M. A., and Bihl, T. J., (2015) “Ethernet Card Discrimination Using Unintentional Cable Emissions and Constellation-Based Fingerprinting,” International Conference on Computing, Networking and Communications (ICNC)
  14. Ward, M. R., Bihl, T. J., Bauer, K. W., “Vibrometry-based vehicle identification framework using nonlinear autoregressive neural networks and decision fusion,” IEEE National Aerospace & Electronics Conference, Dayton, OH, June 2014, pp. 180-185
  15. Bihl, T. J., Mitchell, J.R., and Irwin, R. D., “Hybrid System Identification for MIMO Control-System Design,” 19th IFAC (International Federation of Automatic Control) Symposium on Automatic Control in Aerospace, Würzburg, Germany, September, 2013 
  16. Ryer, D.M., Bihl, T. J., Bauer, K.W., and Rogers, S.K., “QUEST Hierarchy for Hyperspectral Face Recognition,” SPIE Symposium on Defense & Security, Peer Reviewed Biometrics Session, Orlando FL, 2011 
  17. Mindrup, F., Bihl, T. J., and Bauer, K., "Modeling Noise in a Framework to Optimize the Detection of Anomalies in Hyperspectral Imaging," Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 20, 2010, pp. 517-524 
  18. Williams, J., Bihl, T. J., and Bauer, K., "Mitigation of Correlation and Heterogeneity Effects in Hyperspectral Data," Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 20, 2010, pp. 501-507 
  19. Bihl, T. J., Heidenreich, J., Allen, D., and Hunt, K., “SPECTTRA:  A Space Power System Modeling and Simulation Tool,” AIAA 7th International Energy Conversion Engineering Conference, Denver CO, Aug. 2009 
  20. Bihl, T. J., Pham, K.D., and Murphey, T.W., “Modeling and Control of Active Gravity Off-Loading for Deployable Space Structures,” SPIE Symposium on Defense & Security, Orlando FL, 2007 
  21. Bihl, T. J., Manning, W.J., Mitchell, J.R., and Bukley, A.P., “Controller Development and Embedded Controller Implementation for Active Gravity Off-Loading of Deployable Space Structures,” 30th Annual AAS Guidance and Control Conference, Breckenridge CO, 2007

Presentations

  1. Bihl, T. J. (2019) “Artificial Intelligence and Autonomy,” Kittyhawk Chapter of the Association of Old Crows (AOC) Luncheon, Nov., Dayton, OH *invited
  2. Bihl, T. J. (2019) “Finding Algorithm Settings: Easy and Efficient Hyperparameter Optimization to Address some Artificial Intelligence “ilities” Ohio Math Association of America Conference, Shawnee State University, Oct., Portsmouth, OH
  3. Bihl, T. J., Cox, C., Machin, T. (2019) “Towards a Taxonomy of Planning for Autonomous Systems,” INFORMS, Oct., Seattle, WA
  4. Bihl, T. J., DeMange, A., Douglass, S., Fan, D., Hill, K., Jenkins, T., Taha, T., Westberg, S., Yakopcic, C., “Sensing, Decision Making, and Control on the Intel Loihi Spiking Neural Processor” 2019 Neuro Inspired Computational Elements (NICE) Workshop, Albany, NY, accepted
  5. Boehmke, B. C., Bihl, T. J., Gutierrez, R. J., Bauer, K. W., and Saie, C. M. (2017) invited: "Big Cyber Data Analysis:  Developing Embedded Analytics Methods for Efficient Cyber Data Mining" 2017 IEEE National Aerospace and Electronics Conference (NAECON),  Dayton, OH
  6. Bihl, T. J. (2017) “Physical Layer Approaches for Characterizing Communication Devices” 2017 Appalachian Institute of Digital Evidence (AIDE) Conference, Marshall University
  7. Gutierrez, R. J., Bauer, K. W., Boehmke, B. C., Saie, C.M., Bihl, T. J., (2017) "Using Tabulated Vectors and Embedded Analytics for Efficient Cyber Data Mining," 2017 Military Operations Research Society Symposium
  8. Bihl, T. J., (2016) invited: “Biostatistics Using JMP,” Central Ohio JMP User Group (COJUG), Ashland Inc., Nov. 11, Columbus, OH
  9. Bihl, T. J. "MATLAB Tutorial: Introduction and Example AFIT Case Studies," Annual WPAFB Analysis Forum, Air Force Institute of Technology, Dayton, OH, Dec. 2014
  10. Paciencia, T. J., Bihl, T. J., and Bauer, K. W., "Optimizing hyper-radial values to create intuitive n-dimensional visualizations," 2014 MAA Ohio Chapter Meeting, Wittenberg University, Springfield, OH, Oct. 31 - Nov. 1, 2014
  11. Paciencia, T., Bihl, T. J., and  Bauer, K.W., "Improved visualizations of n-dimensional data using hyper-radial values," 2014 Cincinnati-Dayton INFORMS Symposium, Wright State University, August 29, 2014
  12. Bihl, T. J., and Bauer, K.W., “Data Mining and Analyzing Basic Features of the State of the Union Addresses,” 2013 MAA Ohio Chapter Meeting,  Denison University, April 5-6, 2013 
  13. Situ, J.X., Bihl, T. J., Bauer K. W., and Friend, M.A., “Combat Identification of Synthetic Aperture Radar Images using Contextual Features and Bayesian Belief Networks,” 80th Military Operations Research Society Symposium, United States Air Force Academy, June 2012 
  14. Friesen, K., Bihl, T. J., Bauer, K.W., Williams, J., and Friend, M.A., “Automatic Combat Identification and Out of Library Considerations for Hyperspectral Imagery,” 80th Military Operations Research Society Symposium, United States Air Force Academy, June 2012 
  15. Williams, J. P., Bihl, T. J., and Bauer, K. W., “Towards the Mitigation of Correlation Effects in Anomaly Detection for Hyperspectral Imagery,” INFORMS Midwest Conference, Columbus, OH, 2011 
  16. Williams, J. P., Bihl, T. J., and Bauer, K. W., “Towards the Mitigation of Correlation Effects in Anomaly Detection for Hyperspectral Imagery,” MORS Education and Professional Development Colloquium, Lexington, VA, 2011 
  17. Mindrup, F., Bauer, K., Bihl, T. J., and Williams, J., "AFIT/ENS Sensor Fusion Lab Advanced Research in Automatic Target Recognition," 78th Military Operations Research Society Symposium, Quantico, VA, June 2010 
  18. Allen, D., Heidenreich, J., Bihl, T. J., and Hunt, K., “SPECTTRA:  A Space Power System Modeling and Simulation Tool,” Space Power Workshop, April 2009

Posters

  1. Bihl, T. J., Steeneck, D., Jordan, J. (2018) "Multivariate Stochastic Approximation Versus Design Of Experiments For Learning Vector Quantization Hyperparameter Tuning" 2018 INFORMS Conference, Phoenix, AZ
  2. Borchers, C.*, Bihl, T. J., Poon, C., Rohrbach, D. J., Borchers, S., Trevino, J., Rubin, M., Donnelly, H., Kellawan, K., Carpenter, L., Bahl, S., Rohan, C., Muennich, E., Guenthner, S.,  Hahn, H., Rkein, A., Darst, M., Mousdicas, N., Travers, J. B., and Sunar, U., (2018) "Quantifying Photodamage by Noninvasive Mesoscopic Skin Imaging" 2018 Ohio Dermatological Association (ODA) Annual Meeting, Columbus, OH
  3. Bihl, T. J. and Hajjar, S. (2017) “Electricity Theft Concerns within Advanced Energy Technologies,” 2017 IEEE National Aerospace and Electronics Conference (NAECON),  Dayton, OH
  4. Hawkes, T., Bihl, T. J., and Rogers, S., (2016), “Poster: Qualia Exploitation of Sensing Technology (QuEST) for Vehicular Network Optimization,” 2016 IEEE Vehicular Networking Conference (VNC), pp. 1-2
  5. Teixeira, A., Bihl, J., Bihl, T., Ribeiro, R., Kool, R., Schmeler, K., Herzog, T., Goncalves, W., Nicolau, S., and Marques, R., "A Pre and Intraoperative Scoring System to Predict Nodal Metasis in Endometrial Cancer," Society of Surgical Oncology - Annual Cancer Symposium, Boston, MA, March, 2016

Acknowledged in Publications

  1. Johnson, R. J., Williams, J. P., and Bauer, K. W., "AutoGAD: An Improved ICA-Based Hyperspectral Anomaly Detection Algorithm," IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 6, pp. 3492-3503
Professional Affiliations/Memberships: 

Institute for Operations Research and the Management Sciences (INFORMS), Member (2014)

Institute of Electrical and Electronics Engineers (IEEE), Member (2012), Senior Member (2019)

Tau Beta Pi (Engineering Honor Society), Member (2015)

Center for Palladian Studies in America, Member (2011)

Eta Kappa Nu (Electrical Engineering Honor Society), Student Member (2005)

Alpha Kappa Delta (International Sociology Honor Society), Student Member (2003)                         

 

Awards/Recognition: 

Vice President of INFORMS for Chapters/Fora (2020 & 2021)

IEEE Senior Member

Nominated for PECASE

Team Award, AutoWave Project, Kittyhawk Association of Old Crows

Outstanding Young OR/MS Award, Cincy-Dayton INFORMS Chapter - 2017

 

 

 

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