Patrick K. Simpson was born in Cordova, AK in 1964, a small fishing community on the Prince William Sound. In 1980 he moved to Anchorage where he completed high school. From 1974 to 1986, Mr. Simpson worked with his family on fishing boats, starting as a crew member and working his way up to captain.

Mr. Simpson received his Bachelor of Arts degree in Computer Science in 1986 from the University of California at San Diego. Following college, Mr. Simpson distinguished himself in the application of neural networks, fuzzy systems, and artificial intelligence to difficult defense related problems in areas such as electronic intelligence, radar surveillance, sonar signal identification, and various aspects of automated diagnostics.

In addition to his engineering pursuits, Mr. Simpson has written several archival papers, he has taught several courses, he has written a text book that has been used in college courses around the United States, and he has lectured on the theory and application of neural networks and fuzzy systems world wide.

Recently, Mr. Simpson has combined his past with the present and formed Scientific Fishery Systems, Inc., a small business dedicated to the development of technologies for more efficient fisheries.

Experience History

Scientific Fishery Systems, Inc.

1993 - Present. Corporate Officer. Mr. Simpson is the Founder and President of Scientific Fishery Systems, Inc., a small business dedicated to the development of technologies for more efficient fisheries. As President, Mr. Simpson is responsible for all administration, business development, and engineering management. The company has now grown to six employees located in Alaska and Washington.

ORINCON – Principal Engineer

1992 - 1994. New Business Development. Mr. Simpson spent a quarter of his time pursuing new business opportunities at the US Air Force Rome Laboratory. Mr. Simpson was able to build a $1.7M business over two years through contract work in communications, speech processing, radar signal processing, software engineering, electronic intelligence, and data fusion.

1994. Prognastic Methodologies for Mechanical Systems. Mr. Simpson was project leader for the development of a prognostic methodology for predicting faults in helicoper components. This project successfully demonstrated the ability to predict helicopter transmission faults using fuzzy min-max neural networks.

1993 - 1994. Neural Network Vehicle Identification for Loop Data. Mr. Simpson assisted in the comparative evaluation of a neural network based classification system that identified various vehicles from inductance loop data.

1993. Neural Network Data Fusion. Mr. Simpson was project leader in the development of an ultrasound heart monitoring system that utilized hierarchically organized neural networks for tissue identification.

1993 . Low-Frequency Active Acoustics. Mr. Simpson assists in the development of fuzzy min-max and radial basis function classifiers for separating acoustic returns from targets and clutter in the ocean.

1993 . Multisensor Fusion. Mr. Simpson assisted in a demonstration project that developed a multisensor system for ocean surveillance. Contributions included investigation of various signal processing chains and the implementation of neural network classifiers.

1992 - 1993. Miniaturized Implementation of Neural Network for Ocean Target Underwater Recognition (MINOTAUR). Mr. Simpson was project leader for the MINOTAUR program, a three-phase effort designed to provide an acoustic detection and classification capability in a package that is small, lightweight, and inexpensive.

1992: DARPA Acoustic Nontraditional Exploitation System (DANTES) program:. Mr. Simpson is leading investigations into advanced neural network and fuzzy logic technologies for the DARPA DANTES program.

Accurate Automation Corporation – Chief Engineer

1991-1992: Chief Engineer. Mr. Simpson was responsible for $2M in Defense Programs that applied intelligent system technologies to difficult defense-related problems, including radar signal processing, target tracking, sensor data fusion, robotic control, aircraft control, and fault diagnosis. His responsibilities included management of the engineering staff, new business development, and engineering.

Applied Technology Institute – Instructor

1993-1994. Application of Neural Networks and Fuzzy Systems. Mr. Simpson teaches the theory and application of neural networks, fuzzy systems, and their synergistic combinations. Case studies include applications in communication, sonar, radar, virtual reality, and document retrieval.

1990-1992. Introduction to Neural Networks. Mr. Simpson taught a refined short course of earlier UCSD Extension course that emphasizes applications to radar, sonar, and diagnositics.

General Dynamics Electronics Division (GDE) – Engineering Specialist

1988-1991: Neural Network Independent Research and Development. Mr. Simpson was the Principal Investigator of the $2M Neural Network Independent Research and Development Program at GDE. Mr. Simpson’s accomplishments included the creation of new associative memory and spatiotemporal pattern recognition paradigms, development of neural network applications for diagnostics, acoustic pattern recognition, intelligence analysis, and resource optimization. He accepted the additional responsibility of lecturing, consulting, and teaching throughout the corporation. Mr. Simpson wrote extensively on subjects including fuzzy logic, artificial intelligence, knowledge engineering, and neural networks. Additional responsibilities included strategic planning, new business development, and technical reviews.

1990 - 1991: DARPA Sonar Signal Classification Comparative Performance Program. Mr. Simpson was program manager of the $500K DARPA Sonar Signal Classification Comparative Performance Program, a program that explored a wide variety of signal processing and neural network techniques for feature extraction and classification of short-duration passive acoustic events.

1989-1991: WRDC Adaptive Networks Avionics Resource Manager Program. Mr. Simpson was program manager and later program administrator of a $700K Air Force R&D project that was developing neural network techniques for resource allocation in a dense EW environment.

University of California at San Diego Extension – Instructor

1987-1990: Introduction to Neural Networks. An instructor of UCSD Extension's Introduction to Neural Networks course. This course presented a broad overview of more than thirty neural networks paradigms that have proven or potential applications. The course reviewed the primary mathematical tools needed for neural network analysis and provided software for several neural network paradigms.

Ball Systems Engineering Division – Member of Technical Staff

1987-1988: Adaptive Network Cognitive Processor (ANCP) program.. Mr. Simpson managed the Adaptive Network Cognitive Processor (ANCP) program, a project that explored that application of neural networks to a real-time electronic warfare (EW) threat-response environment for use in battlefield interdiction missions. The project focused upon the use of neural network techniques to synergize raw data from the environment with knowledge from the human operator into a coherent system.

Naval Command, Control, and Ocean Surveillance Center– Contractor with UNISYS and SDSU Foundation

1986-1987: Neural Networks Research. Mr. Simpson explored the application of neural networks to speech processing. Work included the implementation of several neural network paradigms and writing a survey of neural networks that later became a book.

1986-1987: Battle Manager Speech Interface program. Mr. Simpson was a technical lead for a portion of the Battle Manager Speech Interface program, a project intended to implement a speech interface to a distributed Sun workstation environment for use in the Strategic Defense Initiative’s (SDI) Command and Control Center.

1986: IRIS Speech Interface. Mr. Simpson designed and implemented a new portion of the Symbolics 3600 (LISP machine) operating system to include a second serial I/O peripheral used for speech input to the IRIS Natural Language Interface.

1985-1986: 1MC/3MC Speaker Database Project. Mr. Simpson designed and implemented a menu-driven PC-based database system for 1MC and 3MC speaker systems onboard the Pacific Fleet’s aircraft carriers.

Family Fishing Boats – Commercial Fisherman

1974-1985. Mr. Simpson worked summers and most school breaks as a commercial fisherman on the family fishing boats off the coast of Alaska from the age of 10 through his junior year of college.

Personal

Married in 1986, three children (ages 11, 9 and 2), active in professional organizations and exercises regularly.

B.A. Computer Science, University of California, San Diego, 1986.

• Simpson, P. (1990). Artificial Neural Systems: Foundations, Paradigms, Applications and Implementations, McGraw-Hill: New York (previously Pergamon Press: Elmsford, NY).
• Simpson, P. (1995), edited, Technology Update Series: Neural Networks Theory, Technology and Applications, IEEE Press, Piscataway, NJ..
• Simpson, P. (1995), edited, Technology Update Series: .Neural Networks Applications, IEEE Press, Piscataway, NJ.
• Eberhart, R., Dobbins, R. & Simpson, P. (1996). Computational Intelligence, Academic Press, Boston MA.

• Simpson, P. (1988). Bidirectional associative memory systems, Heuristics, Vol. 1, No. 2, pp. 52-60.
• Simpson, P. & Deich, R. (1989). Battlefield surveillance using the GDE1 neural network, Intelligent Systems Review, Vol 1, No. 3, pp 3-13.
• Simpson, P. (1989). Connectionist expert systems: Neural network and expert system synergy, Intelligent Systems Review, Vol. 2, No. 1, pp. 46-51.
• McDuff, R. & Simpson, P. (1990). An adaptive resonance diagnostics systems, The Journal of Neural Network Computing, Vol. 2, No. 1, pp. 19-29.
• Simpson, P. (1990). Higher-ordered and intraconnected bidirectional associative memories, IEEE Trans. on Systems, Man, and Cybernetics, Vol. 20, pp. 637-653.
• Simpson, P. (1991). Neural networks for ocean engineering, IEEE Transactions on Neural Networks, Vol. 2, No. 2, pp. 179-180.
• Simpson, P. (1991). Fuzzy min-max classification with neural networks, Heuristics, Vol. 4, No. 1, pp. 1-9.
• Simpson, P. (1992). Fuzzy min-max neural networks: 1. Classification, IEEE Transactions on Neural Networks, Vol. 3, No., 5, pp. 776-786.
• Simpson, P. (1992). Guest Editor’s Introduction: Neural Networks for Oceanic Engineering, IEEE Journal of Oceanic Engineering, Vol. 17, pp. 297-298.
• Simpson, P. (1993). Fuzzy min-max neural networks: 2. Clustering, IEEE Transactions on Fuzzy Systems, Vol. 1, No. 1, pp. 32-45.
• McBeth, J., Luse, S. & Simpson, P. (1993). Classifying sonar signals with the fuzzy min-max neural network, U.S. NavyJournal of Underwater Acoustics, Vol. 43, No. 2, pp. 799-811.
• Brotherton, T., Pollard, T., Simpson, P. & DeMaria, T. (1994). Classifying tissue and structure in echocardiograms, IEEE. Engineering in Medicine & Biology, Vol. , No. , pp. 754-760.

• Simpson, P. (1989). Neural networks, Chapter 7 in Standards and Review Manual for Certification in Knowledge Engineering, M. White & J. Goldsmith, Eds., Rockville: The Systemsware Corporation, pp. 108-136.
• Simpson, P. (1989). The Hardware of AI. Section II: Neural Net Hardware,Chapter 31 in Standards and Review Manual for Certification in Knowledge Engineering, M. White & J. Goldsmith, Eds., Rockville: The Systemsware Corporation, pp. 490-499.
• Simpson, P. (1990). Neural networks for sonar signal processing, Chapter 20 in Handbook of Neural Computing Applications, Maren, A., Pap, R. & Hartson, C., pp. 313-329, San Diego: Academic Press.
• Simpson, P. (1992). Foundations of neural networks, Chapter 1 in Artificial Neural Networks, Lau, C. & Sanchez-Sinencio, E. (Eds.), pp. 2-13, IEEE Press, New York, NY.

• Simpson, P. (1988). Highlights of the First Annual International Neural Network Society Meeting, General Dynamics AI Quarterly, p. 10.
• Simpson, P. (1989). Classification of spectral patterns with a bidirectional associative memory, Neural Network Review, Vol. 3, No. 3, pp. 127-128.
• Simpson, P. (1990). Response to "A system of associative memories based on orthogonality of patterns," Neural Network Review, Vol. 4, No. 1, pp. 44-45.
• Simpson, P. (1991). "Neural Computing Architectures" edited by I. Aleksander, The Journal of Neural Network Computing, Vol. 2, No. 3, pp. 52-55.
• Simpson, P. (1991). "Self-Organization and Associative Memory: Third Edition" by T. Kohonen, The Journal of Neural Network Computing, Vol. 2, No. 4, pp. 41-45.
• Simpson, P. (1991). "Neurocomputing" by R. Hecht-Nielsen, IEEE Trans. on Neural Networks, Vol. 2, No. 4, pp. 476-477.

• Simpson, P. (1988). Artificial intelligence and artificial neural systems, General Dynamics AI Quarterly, pp. 17-22.
• Simpson, P. (1990). Hiring new college graduates: One employers perspective, ISSNNet Feature Article, International Student Society for Neural Networks Newsletter, Vol 1., No. 2, pp. 1-2.
• Simpson, P. (1995). President’s Message - A Personal Invitation, CoNNections - The Newletter of the IEEE Neural Networks Council, IEEE, March - April.
• Simpson, P. (1995). President’s Message - Should the Council Become a Society?, CoNNections - The Newletter of the IEEE Neural Networks Council, IEEE, June - July.

• Taber, W., Deich, R., Simpson, P., & Fagg, A. (1988). The recognition of orca calls with a neural network, Proceedings of the International Workshop on Fuzzy Systems Applications, Iizuka City, Japan, August 21-24.
• Edson, B., Turner, C., Meyers, M., & Simpson, P. (1988). The adaptive network cognitive processor, Proceedings of the 1988 Aerospace Applications of Artificial Intelligence (AAAIC 88), Dayton SIGART, Dayton, OH, October 25-27.
• Simpson, P. & Deich, R. (1988). Neural nets, fuzzy logic and acoustic pattern recognition, Proceedings of the 1988 Aerospace Applications of Artificial Intelligence (AAAIC 88), Dayton SIGART, Dayton, OH, October 25-27.
• Simpson, P. (1989). Combined and diffeo-quadratic Hebbian neural systems, IEEE WESCON '89 Conference Record, pp. 695-699.
• Simpson, P. (1989). Associative memory systems, Proceedings of the 1990 International Joint Conference on Neural Networks (IJCNN-90-WASH-DC), Vol. 1, pp. 468-471, Lawrence Erlbaum Associates, Hillsdale.
• McDuff, R. & Simpson, P. (1989). Using neural networks for F-16 fault diagnosis: I. System description, Proceedings of AUTOTESTCON '89, Vol. 1, pp. 532-545.
• McDuff, R. & Simpson, P. (1989). An adaptive resonance diagnostics system, Fifth Annual AAAI Conference Proceedings: Volume II, (pp. 106-124), October 23-24, Dayton SIGART, Dayton, OH.
• McDuff, R. & Simpson, P. (1990). Using neural networks for F-16 fault diagnosis: II. Simulation Results, SPIE Proceedings Volume 1294: Applications of Neural Networks, Rogers, S., Ed., pp. 42-55.
• Fields, R.L., Yoerger, E.J. & Simpson, P. (1990). Performance of neural networks in classifying environmentally distorted transient signals, Proceedings of OCEANS '90, Arlington, VA.
• Simpson, P. (1990). Cauchy node backpropagation, IEEE WESCON '90 Conference Record, pp. 270-273.
• Rush, G., Pitts, C. & Simpson, P. (1990). ECM resource management for self-protection, Proceedings of GD AI 90, Ft. Worth, TX, November 7-8, 1990.
• Simpson, P. (1990). Fuzzy adaptive resonance theory, Proceedings of GD AI 90, Ft. Worth, TX, November 7-8, 1990.
• Simpson, P. (1991). Neural network paradigms, AGARD Lecture Series 179: Artificial Neural Network Approaches in Guidance and Control, AGARD-LS-179, NATO Publication, London, UK.
• Simpson, P. (1991). Multisensor data fusion as applied to guidance and control, AGARD Lecture Series 179: Artificial Neural Network Approaches in Guidance and Control, AGARD-LS-179, NATO Publication, London, UK.
• Simpson, P. (1991). Fuzzy min-max classifiers, Proceedings of the Conference on Neural Networks for Ocean Engineering, Washington, DC, August 15-17, 1991, pp. 291-300.
• Simpson, P. (1991). Fuzzy min-max neural networks, Proceedings of the 1991 International Joint Conference on Neural Networks - Singapore, November 18-22, 1991, Singapore.
• Simpson, P. & McBeth, J. (1992). Fuzzy min-max neural networks for nonlinear pattern classification: recent refinements, Proceedings of WNN-AIND 92, February 10-12, 1992, Auburn, AL, pp. 479-489.
• Simpson, P. & Jahns, G. (1992). Fuzzy min-max neural networks for function approximation, 1993 IEEE International Conference on Neural Networks, March 28 - April 1, 1993.
• Fogel, D. & Simpson, P. (1992). Evolving fuzzy clusters, 1993 IEEE International Conference on Neural Networks (ICNN-93), March 28 - April 1, 1993, San Francisco.
• Simpson, P. & Fogel, D. (1993). Experiments with evolving fuzzy clusters, Second Annual Conference on Evolutionary Programming, February 25-26, 1993, San Diego, CA.
• Brotherton, T., Fogel, D., Simpson, P. & Pollard, T. (1994). Applying evolutionary programming techniques to classifier design, Third Annual Conference on Evolutionary Programming, February 23-25, 1994, San Diego, CA.
• Owen, D., Simpson, P., & Perlow, D. (1994). Practical considerations on neural network class generalization, SBIR Conference, Crystal City, VA, June.
• Brotherton, T. & Simpson, P. (1995). Dynamic feature set training of neural nets for classification, Fourth Annual Conference on Evolutionary Programming, Feb 28 - Mar 1, San Diego, CA.
• Froning, J., Brotherton, T., Simpson, P., Froelicher, V. & Do, D. (1994). Classification of CAD serinity using fusion neural net analysis of multiple exercise ECG waveform representations, Annual Computers in Cardiology Conference, Santa Barbara, CA.
• Reichart, S., Simpson, P. & Brotherton, T. (1995). Acoustic charge transport implementation of neural networks for signal processing, IEEE Dual-Use Technology Conference, Rome, NY.
• Brotherton, T., Simpson, P., Froning, J. & Froelicher, V. (1995). Fuzzy neural net processing of exercise test ECG to determine the severity of coronary artery disease, VI Int’l Fuzzy Systems Assoc. World Congress, Sao Paolo, Brazil.
• Simpson, P., & Brotherton, T. (1995). Fuzzy neural network machine prognosis, SPIE Applications of Fuzzy Logic Technology II, April 17-21, Orlando, FL.
• Denny, G. & Simpson, P. (1998). Broadband sonar fish identication, 1998 Annual Meeting of the Acoustical Society of America, by invitation, June 26, 1998, Seattle, WA.

• Simpson, P. (1986). The parallel distributed processing model: Is it good enough to model the real world?, unpublished monograph.
• Simpson, P. (1986). IRUS speech recognition interface: Final report, Naval Ocean Systems Center, Code 441, unpublished technical report.
• Simpson, P. (1987). A survey of artificial neural systems, Naval Ocean Systems Center. Technical Document, TD-1106.
• Bergstrom, A., Boaz, R., Payne, H., & Simpson, P. (1987). Relocatable targets and artificial intelligence, Verac Technical Report.
• Myers, M., Turner, C., Kuczewski, R., & Simpson, P. (1988). ANCP Adaptive Network Cognitive Processor: Volumes I & II, TRW MEAD, Final Report prepared for Air Force Wright Aeronautical Laboratories.
• McDuff, R. & Simpson, P. (1988). Using neural networks for F-16 fault diagnosis, Final Report of Phase I, Air Force Human Resources Laboratory.
• Deich, R., Elzenga, R., McDuff, R. & Simpson, P. (1988). Neural networks IR&D, General Dynamics Electronics Division, Engineering Research Report #R-88-041.
• Simpson, P. & Deich, R. (1989). Neural Networks IR&D Brochure, General Dynamics Electronics Division Independent Research and Development Program - 1989, pp. 347-372. (Received a score of 7.9 out of 10 - highest rated returning IR&D project in the Division).
• Simpson, P. (1990). The error-correction additive Grossberg neural system, General Dynamics Technical Report, GDE-ISG-PKS-09.
• Simpson, P. (1990). Neural Networks IR&D Brochure, General Dynamics Electronics Division Independent Research and Development Program - 1990, pp. 41-62. (Received a score of 7.7 out of 10).
• Simpson, P. (1990). The GDE2 neural network: An on-line learning spatiotemporal pattern classifier, General Dynamics Technical Report GDE-ISG-PKS-10.
• Simpson, P. (1990). The GDE3 neural network: A spatiotemporal pattern classifier, General Dynamics Technical Report GDE-ISG-PKS-12.
• Simpson, P. (1991). Neural Networks IR&D Brochure, General Dynamics Electronics Division Independent Research and Development Program - 1991, pp. 11-16.
• Atkins, M. & Simpson, P. (1991). Design considerations for fault diagnosis with neural networks on the National Aero-Space Plane (NASP), submitted to Accurate Automation Corporation and published as a portion of there Final Technical Report entitled "Neural Networks applied to fault diagnosis in aeronautical systems," June 1991, Report No. 91-AAC008, NASP Joint Program Office, WPAFB, OH.
• Simpson, P. (1993). Minituarized Implementation of Neural Network Ocean Acoustic Recognition (MINOTAUR) System, Final Report, Naval Command, Control and Ocean Surveillance Center, March.
• Simpson, P., Brotherton, T., Pollard, T. & Haines, K. (1993). Neural Network Data Fusion Phase II, Final Report, Advanced Research Projects Agency, December.
• Simpson, P. & Brotherton, T. (1994). Prognostic Methodologies for Mechanical Systems, SBIR Phase I Final Report, U.S. Army Test Measurement and Development Engineering (TMDE), Huntsvill, AL, September.
• Simpson, P., Kreger, A. & Brotherton, T. (1995). Acoustic Charge Transport Implementation of Neural Networks, SBIR Phase I Final Report, US Air Force, Rome Laboratory, January.
• Simpson, P. (1994). Application of Defense Technologies to the Fisheries, Project No. SFS-94-01, SBIR Phase I Final Report, Award No. III-9360489, National Science Foundation, Arlington, VA, November.
• Simpson, P. (1995). Fisheries Management Geographic Information Systems, Report No. SFS-95-03, SBIR Phase I Final Report, Award No. DMI-9460932, National Science Foundation, Arlington, VA, July.
• Simpson, P., Ruggerone, G. & Freeberg, M. (1995). Neural Network Fish Return Forecasting, Report No. SFS-95-02, Phase I SBIR Final Report, Award No. DMI-9461197, National Science Foundation, Arlington, VA, July.
• Simpson, P. and Tuohey, M (1996). Broadband Freshwater Fish Identification, Report No. SFS-95-05, National Biological Service, Great Lakes Science Center, Work Order No. 84080-6-0584, December.
• Simpson, P. & Penvenne, J. (1996). Automated Broadband Bottomfish Identification, Report No. SFS-95-04, Phase I SBIR Final Report, Dept. of Commerce, Contract No. 50-DKNA-5-00096, 30 January.
• Simpson, P. & Penvenne, J. (1996). Broadband Fish Identification Prototype, Report No. SFS-95-01, Phase I SBIR Bridge Grant Final Report, Alaska Science and Technology Foundation, Award No. 94-4-121R, Anchorage AK, 31 January.
• Denny, G., deVilleroy, K, & Simpson, P. (1997). Long Range Tuna School Detection, Report No. SFS-97-01, Saltonstall-Kennedy Project Final Report, National Marine Fisheries Service, Southwest Fisheries Science Center, November.
• Simpson, P. & Denny, G. (1998). Application of Defense Technologies to the Fisheries - Phase II, Report No. SFS-96-05, Phase II SBIR Final Report, Award No. DMI-9503656, National Science Foundation, September.
• Simpson, P. & Denny, G. (1998). Automated Broadband Identification of Bottomfish, Report No. SFS-96-07, Phase II SBIR Final Report, Contract No. 50-DKNA-6-90140, U.S. Department of Commerce, September.

• Simpson, P. (1988). Battlefield surveillance with acoustic and seismic sensors, prepared for the Army Research Office, General Dynamics Technical Report GDE-ISG-PKS-01.
• Simpson, P. (1988). General Dynamics Artificial Intelligence Center Intelligent Systems Group 1988 Capabilities Brochure, General Dynamics Technical Report GDE-ISG-PKS-04.
• Simpson, P. (1989). Submarine communication using mammal emissions, prepared for General Dynamics Underseas Warfare Center, General Dynamics Technical Report GDE-ISG-PKS-06.
• Smith, E., Simpson, P. & Deich, R. (1990). Government programs, laboratories, and points of contact for acoustic signal classification with neural networks, General Dynamics Technical Report GDE-ISG-EAS-01.
• Simpson, P. & Nunally, P. (1990). Wafer scale integration implementation of the fuzzy ART neural network, prepared for Naval Ocean Systems Center, General Dynamics Technical Report GDE-ISG-PKS-13.
• Simpson, P., McBeth, J.H., Luse, S.A., & Brown, M. (1990). Neural network preprocessing techniques for sonar signal detection and classification, prepared for Defense Advanced Research Projects Agency, General Dynamics Technical Report GDE-ISG-PKS-14.
• Simpson, P., Culver, R. & Nunally, P. (1990). A neural hardware implementation of bistatic radar target localization and tracking for low intensity conflict, prepared for Wright Research and Development Center, General Dynamics Technical Report GDE-ISG-PKS-15.
• Simpson, P. (1992). The application of anti-submarine warfare technology to fish classification and monitoring, ORINCON Corporation, May.
• Simpson, P., Pollard, T., & Katz, N. (1992). Exploring Image Understanding/Neural Network Hybrids, prepared for DARPA, December.
• Simpson, P. (1992). The application of neural networks to adaptive equalization, prepared for U.S. Air Force Rome Laboratories, RL/C3BA, May.
• Simpson, P. (1992). The application of combined extended Kalman filter and neural networks for network flow control, prepared for U.S. Air Force Rome Laboratories, RL/C3BA, May.
• Simpson, P. & Samant, V. (1993). Acoustic Charge Transport (ACT) investigations in RIPPEN/PRIISM, prepared for U.S. Air Force Rome Laboratories, RL/C3BA, May.
• Simpson, P. (1993). Fuzzy Systems Applications to Communications, prepared for U.S. Air Force Rome Laboratories, RL/C3BA, May.
• Simpson, P. (1993). Background Audio Signal Identification Through Multi-Feature Fusion, prepared for U.S. Air Force Rome Laboratories, RL/IRAA, May.
• Simpson, P. & Pollard, T. (1993). Speaker Identification Through Multi-Feature Fusion, prepared for U.S. Air Force Rome Laboratories, RL/IRAA, May.
• Simpson, P. (1993). Channel Characterization with Multi-Feature Fusion for Channel Normalization, prepared for U.S. Air Force Rome Laboratories, RL/IRAA, May.
• Simpson, P. & Krieger, A. (1993). Channel Normalization Evaluation for Selecting the Appropriate Channel Normalization Technique, prepared for U.S. Air Force Rome Laboratories, RL/IRAA, May.
• Simpson, P. & Katz, N. (1993). Translating Khoros Routines into RIPPEN/PRIISM Tools, prepared for U.S. Air Force Rome Laboratories, RL/IRRE, May.
• Simpson, P. (1993). RIPPEN/PRIISM Implementation at RL/IRRE, prepared for U.S. Air Force Rome Laboratories, RL/IRRE, May.
• Simpson, P. & Pollard, T. (1993). Adaptive Fuzzy Neural Control of Call Admission in an ATM Network, prepared for U.S. Air Force Rome Laboratories, RL/C3D, May.
• Simpson, P. (1993). Nontraditional processing of ELINT signals, prepared for U.S. Air Force Rome Laboratories, RL/IRAP, June.
• Simpson, P. (1993). Long-range tuna detection and identification, prepared for NOAA/NMFS/SWFS, March.
• Simpson, P. (1994). Application of defense technologies to the fisheries, prepared for NOAA/NMFS, February.
• Simpson, P. (1997). Long-Range Fish School Detection, prepared for Senator Stevens for NMFS, November.

• Simpson, P. & Edson, B. (1988). Knowledge combination using fuzzy cognitive maps, Proceedings of the Third Annual Workshop on Conceptual Graphs, p. 4.13.
• Simpson, P. (1988). An algorithm for encoding an arbitrary number of patterns in a system of discrete bidirectional associative memories, Neural Networks - Special Supplement for the 1988 INNS Annual Meeting, p. 220.
• Simpson, P. (1989). Combined and diffeo-quadratic Hebbian neural systems, Proceedings of 1989 International Joint Conference on Neural Networks: Vol. II, Washington, DC, pg 583.
• Simpson, P., Luse, S. & Edelstein, M. (1990). Sonar signal classification with the GDE2 neural network, First Government Neural Network Workshop, Naval Ocean Systems Center, San Diego, CA, August 29-31, 1990.
• Pitts, C., Rush, G. & Simpson, P. (1990). Adaptive network avionics resource manager (ANARM) using a backpropagation network, First Government Neural Network Workshop, Naval Ocean Systems Center, August 29-31, 1990.
• Simpson, P., Luse, S., Edelstein, M., & Stockdale, L. (1991). Classification results for short-duration sonar events using neural networks and fuzzy logic, Second Government Neural Network Workshop, U.S. Army Missile Command, Huntsville, AL, September 10-12, 1991.
• Simpson, P., Tuohey, M., & Fleischer, G. (1997). Experiments with broadband fish identification, special session on fisheries hydroacoustics, International Association of Great Lakes Researchers Annual Meeting, Buffalo, June.
• Denny, G., deVilleroy, K. & Simpson, P. (1999). The Advantages of Broadband Sonar for Riverine Fish Stock Assessment, Riverine Sonar Workshop, UW Applied Physics Laboratory, Seattle, WA, February 15-17.

• Simpson, P. & Parra,, J. (1993). Acoutic Method and Apparatus for Identifying Human Sonic Sources, continuation-in-part of U.S. application Serial No. 07/658,642, filed February 22, 1991 and continued as 07/688,395 on 26 February, 1993; status unknown.
• Simpson, P. (1993). Active Broadband Acoustic Method and Apparatus for Identifying Aquatic Life, Awarded December 27, 1993.

• Introduction to neural networks, Guest Lecturer, UCSD Extension, San Diego, CA, Fall 1987.
• Introduction to neural networks, Instructor, UCSD Extension, San Diego, CA, Winter 1988, Fall 1988, Spring 1989, Fall 1989, Spring 1990, & Fall 1990.
• Neural Networks Short Course, General Dynamics Electric Boat Division, East Lyme, CT, October 25-27, 1988.
• A broad overview of neural networks, Office of Secretary of Defense, Weapons Support Improvements Group, Arlington, VA, March 7-8, 1989.
• A broad overview of neural networks, General Dynamics, Defense Initiatives Office & Underwater Warfare Center, Washington, DC, March 9, 1989.
• Neural Nets for Expert Systems, First Annual Conference of the International Association of Knowledge Engineers, College Park, MD, June 26, 1989.
• Introduction to Neural Networks: With an emphasis on applying neural networks to DoD related problems, General Dynamics Electronics Division, San Diego, CA, December 11-13, 1989.
• Introduction to Neural Networks: With an emphasis on applying neural networks to DoD related problems, Rome Air Development Center, Griffiss AFB, NY, March 19-22, 1990.
• Hybrid neural networks for signal processing and diagnostics, one of several lectures in the course Neural Networks: Translating theory to real-world applications, UCLA Extension, Los Angeles, CA, October 16, 1990 & Dallas, TX, September 6, 1991.
• Neural networks: An introduction with applications, General Dynamics Artificial Intelligence Working Group, GDAI-90, Ft. Worth, TX, November 6, 1990.
• Introduction to Neural Networks: Algorithm foundations, paradigms, applications and implementations, Applied Technology Institute, College Park, MD, November 12-14, 1990; San Diego, CA, February 12-14, 1991; Naval Air Development Center, Warminster, PA, May 20-22, 1991; and New London, CT, June 11-13, 1991.
• Neural Networks for Sensor Fusion, 1992 International Joint Conference on Neural Networks, Baltimore, MD, June 7, 1992.
• Neural Networks: Theory and Ocean Surveillance Applications, Oceans 92, Newport, RI, October 26, 1992 (with V. Porto).
• Neural networks and fuzzy systems, in-house course, ORINCON Corporation, San Diego, CA, February - May, 1993.
• Applications of Neural and Fuzzy Systems, Applied Technology Institute, San Diego, CA, April 13-15, 1993; San Diego, CA, February 7-9, 1994; Washington, DC, February 8-10, 1995.
• Neural Networks: Theory and Ocean Surveillance Applications, Oceans 93, Vancourver, BC, CANADA, October (with V. Porto).
• Fuzzy Neural Networks for Hierarchical Fusion, MFI 94, Las Vegas, NV, October 2, 199 (with T. Brotherton).
• Winning SBIR Strategies, a short course offered with Alaska Tech Transfer Assistance Center twice a year since 1996, Usually in April and August.
• Neural Networks, Semester Graduate Course in Computer Science, University of Alaska Anchorage, Winter 1997.

• Bidirectional associative memory systems, General Dynamics Fall AI Working Group, September 28, 1988.
• Neural network applications for defense related problems, 1988 WESCON, Session on Government and Industrial Perspectives of Neural Networks, November 17, 1988.
• Neural networks and acoustic signal processing, San Diego Acoustic Society, December 1, 1988.
• Brief overview of neural network applications, General Dynamics Neural Network Working Group, February 15, 1989.
• Near-term and long-term applications of neural networks, Impacts Technology Symposium on Neural Networks, Chattanooga, TN, April 25, 1989.
• Neural networks at General Dynamics Electronics Division, General Dynamics Neural Networks Symposium, Pomona, CA, May 4, 1989.
• Defense applications of neural networks, Neural Networks for Defense Symposium, Washington, DC, June 17, 1989.
• Artificial Neural Systems: A discussion of the book, San Diego Special Interest Group in Artificial Neural Systems, San Diego, CA, November 16, 1989.
• Fuzzy Adaptive Resonance Theory, Neuroengineering Workshop, Southern Illinois University, Carbondale, IL, September 6-7, 1990.
• Launching a Career from a Degree in Cognitive Science, Career Services Center Panel Discussion, University of California, San Diego, November 5, 1990.
• Fuzzy Pattern Classification, Johns Hopkins University, Applied Physics Laboratory, November 12, 1990.
• Neural networks, National Management Association, Engineers Night, San Diego, CA, February 20, 1991.
• Fuzzy Adaptive Min-Max Unsupervised Classifier, Fuzzy Special Interest Group, San Diego, CA, April 18, 1991.
• Fuzzy Min-Max Neural Networks, International AMSE Conference on Neural Networks: Methodologies and Applications, Association for the Advancement of Modelling and Simulation techniques in Enterprises, San Diego, CA, May 31, 1991.
• Neural networks for ocean engineering, San Diego Chapter of the Oceanic Engineering Society, San Diego, CA, September 13, 1991.
• Neural networks and fuzzy logic, IEEE Power Engineering Society, Chattanooga, TN, December 12, 1991.
• Fuzzy min-max neural networks, ORINCON Seminar, San Diego, CA, January 31, 1992.
• Fuzzy min-max neural networks: 1. Classification, Invited presentation to coincide with IEEE Trans. on Neural Networks Special Issue on Fuzzy Systems, FUZZ-IEEE 92, San Diego, CA, March 11, 1992.
• Fuzzy min-max neural networks, Phonix Fuzztival '92, Regional Interest Group of the IEEE Neural Networks Council, Phoenix, AZ, May 16, 1992.
• Fuzzy sets and pattern recognition, Evolutionary Programming Course, UCSD Extension, October 19, 1992.
• Design methodologies for neural network applications, IEEE Neural Networks Council Computational Intelligence Seminar, Phoenix, AZ, December 4, 1992.
• Fuzzy min-max neural networks, Naval Command, Control, and Ocean Surveillance Center, February 23, 1993.
• From Artificial Intelligence to Computational Intelligence, IEEE San Diego Section Monthly Meeting, November 17, 1993.
• Fuzzy Min-Max Neural Networks, University of Washington, Seattle, WA, May 5, 1994 (televised locally).
• Fuzzy neural networks for predictive diagnostics,1994 World Congress on Computational Intelligence, Orlando, FL, June 28, 1994.
• The State of the IEEE Neural Networks Council, Presidential Address, 1994 World Congress on Computational Intelligence, Orlando, FL, June 29, 1994.
• Biomedical Applications of Neural Networks, Plenary Address, 1994 World Congress on Computational Intelligence, Orlando, FL, June 30, 1994.
• Computational Intelligence and the IEEE Neural Networks Council, Adaptive Controls for Energy and Environment, Sponsored by DOE, Pittsburg, PA, October 24, 1994.
• From ASW to Medicine: Commercializing Defense Technologies, ANNIE 94, St. Louis, MO, November 1994.
• Winning SBIR Stragegies, Alaska Inventors and Entrepreneurs Association, Anchorage AK, Feb. 22, 1996.
• The SBIR Program, Growing Alaska’s Economy, First Annual Symposium, Anchorage AK, March 20, 1996.
• Computational Intelligence in Alaska, IEEE Alaska Section, Anchorage AK, January 17, 1996.
• Do you know where your fish are?, Alaska Association of Photogrammetry and Remote Sensing, Anchorage AK, January 9, 1997.
• Winning with the SBIR Program, Alaska High-Tech Business Council, Anchorage AK, Feb 9, 1997.
• Defense Technologies Applied to the Fisheries, Alaska AFCEA Section, March 1997.
• Neural Networks, Seminar on Complexity, University of Alaska Anchorage, January 22.

• Lead Volunteer International Conference on Neural Networks, San Diego, CA, June 6-10, 1987.
• Tutorials Chair 1988 International Conference on Neural Networks, San Diego, CA, July 23-27, 1988.
• Program Committee Annual Internatioinal Association of Knowledge Engineers Conference, College Park, MD, June 26-28, 1989.
• Conference Chair SPIE Applications of Neural Networks Conference, Orlando, FL, April 16-20, 1990.
• Local Arrang. Chair International Joint Conference on Neural Networks, San Diego, CA, June 17-21, 1990.
• Conference Chair SPIE Applications of Artificial Neural Networks Conference, Orlando, FL, April 1-5, 1991.
• Program Chair IEEE Conference on Neural Networks for Ocean Engineering, Washington, DC, August 15-17, 1991.
• Program Committee International Joint Conference on Neural Networks, Singapore, November 18-22, 1991.
• Org. Committee International Conference on Artificial Neural Networks in Engineering (ANNIE 91), St. Louis, MO, November 10-12, 1991.
• Finance Committee IEEE International Fuzzy Systems Conference (FUZZ-IEEE 92), March 3-5, 1992.
• Conference Chair SPIE Applications of Artificial Neural Networks Conference, Orlando, FL, April 20-24, 1992.
• Conference Chair SPIE Science of Artificial Neural Networks Conference, Orlando, FL, April 20-24, 1992.
• Org. Committee International Conference on Artificial Networks in Engineering (ANNIE 92), St. Louis, MO, November 15-18, 1992.
• Organizer IEEE Neural Networks Council Computational Intelligence Seminar, Phoenix, AZ, December 4, 1992.
• Program Committee EP '93 - The Second Annual Conference on Evolutionary Programming, San Diego, CA, February 25-26, 1993.
• Program Committee 1993 IEEE International Conference on Neural Networks (ICNN-93), San Francisco, March 28 - April 1, 1993.
• Conference Chair SPIE Applications of Artificial Neural Networks Conference, Orlando, FL, April 1993.
• Conference Chair SPIE Science of Artificial Neural Networks Conference, Orlando, FL, April 1993.
• Organising Comm. Third Annual Conference on Artificial Neural Networks, Brighton Conference Centre, UK, May 25-27, 1993.
• Technical Committee 1993 Australian and New Zealand Intelligent Information Systems Conference (ANZIIS 93), Perth Australia, 1993.
• Publicity Co-Chair Third Annual Conference on Evolutionary Programming (EP 94), San Diego, CA, February 23-25, 1994.
• Publicity Chair IEEE International Conference on Evolutionary Computation (ICEC 94), Orlando, FL, July 1994.
• Technical Committee 1994 Australian and New Zealand Intelligent Information Systems Conference (ANZIIS 94), Perth Australia, 1993.
• Program Committee Conference on Computational Intelligence for Financial Engineering, New York City, NY, April 9-11, 1995.
• Program Committee IEEE International Conference on Evolutionary Computation (ICEC 95), Perth Australia, December 12-14, 1995.
• Conference Chair SPIE Fuzzy Systems Applications, Orlando, FL, April 1995.
• General Chair 1998 IEEE World Congress on Computational Intelligence, Anchorage, AK, May 4-9.

• Chairman Computer Society, IEEE San Diego Section (1988 - 1989).
• Treasurer IEEE Neural Networks Council (1990 - 1991).
• Vice-President IEEE Neural Networks Council (1992 - 1993).
• President IEEE Neural Networks Council (1994)
• Past-President IEEE Neural Networks Council (1995 - 1996)

• Editorial Board The Journal of Neural Network Computing (1989 - 1991).
• Book Review Editor The Journal of Neural Network Computing (1990 -1991).
• Associate Editor IEEE Trans. on Neural Networks (1991 - 1995).
• Guest Editor Special Issue on Neural Networks for Oceanic Engineering, IEEE Journal of Ocean Engineering, Fall 1992.
• Editorial Board The Australian Journal of Intelligent Information Processing Systems (1993 - Present).

• IEEE Transactions on Neural Networks
• IEEE Transactions on Fuzzy Systems
• IEEE Transactions on Systems, Man, and Cybernetics
• IEEE Transactions on Circuits and Systems
• IEEE Journal of Oceanic Engineering
• IEEE Spectrum
• Journal of Intelligent Manufacturing
• Neural Network Review
• The Journal of Neural Network Computing
• Neural Networks
• International Journal of Approximate Reasoning
• Nuclear Technology
• International Journal of Fuzzy Sets and Systems
• International Fuzzy Systems Journal
• Medical Engineering and Physics

• International Neural Networks Conference (INNC 90), Paris, France, June 1990.
• Conference on Neural Networks for Ocean Engineering (CNNOE 91), Washington, DC, August 1991.
• Artificial Neural Networks in Engineering (ANNIE 91), St. Louis, MO, November 1991.
• International Joint Conference on Neural Networks (IJCNN 91), Singapore, November 1991.
• RNN/IEEE Rostov-on-Don Neural Network Symposium, Rostov-on-Don, Russia, Nov. 1992.
• IEEE International Conference on Neural Networks (ICNN 93), San Francisco, CA, March 1993.
• IEEE International Fuzzy Systems Conference (FUZZ-IEEE 93), San Francisco, CA, March 1993.
• Annual International Evolutionary Programming Conference (EP 94), San Diego, CA, February 18-19, 1994.
• Australian and New Zealand Intelligent Information Systems Conference (ANZIIS 94), Perth Australia, November 1994.

• National Science Foundation
• University of California, MICRO Program
• National Oceanic and Atmospheric Administration

• UNIX for Systems Programmers, UCSD Extension, Winter 1987.
• Leadership Training, General Dynamics Electronics and the National Management Association, 1990.
• Career Development, General Dynamics Data Systems Division, August 9, 1990.
• Systems Engineering Seminar, General Dynamics Corporate Headquarters, September 30 - October 6, 1990.
• Total Quality Management, General Dynamics Electronics Division, August 8, 1991.

• Institute of Electrical and Electronics Engineers (IEEE)
• International Neural Network Society (INNS)
• International Association of Knowledge Engineers (IAKE)
• International Society for Optical Engineering (SPIE)
• Evolutionary Programming Society (EPS)
• American Fisheries Society (AFS)

• Lecturer AGARD Lecture Series 179: Artificial Neural Network Approaches in Guidance and Control, Albert J. Shapiro, Lecture Series Director, Monterey, CA, Oslo, Norway, and Hamburg, Germany, October 7-19, 1991.
• Member Who's Who in Science and Engineering, 1991.
• Member The International Who’s Who of Intellectuals, - Eleventh Edition, 1994.
• Member Men of Achievement, Sixteenth Edition, 1994.
• Member Dictionary of International Biography - Twenty-third Edition, 1994.
• Member Who’s Who Worldwide, 1994.
• Member Sterling’s Who’s Who,1994.
• Member Who’s Who in the West, Silver Anniversary 25th Edition, 1994.