2023

1. J.A. Crowder and M.J. Hirsch, “A Spatio-Temporal Memory System for Multi-Modal Sensor Fusion,” to appear in Transactions on Computational Science and Computational Intelligence, 2023.
2. J.A. Crowder and M.J. Hirsch, “The Rasmussen Cognition Model as a Framework for a Modified OODA Loop,” to appear in Transactions on Computational Science and Computational Intelligence, 2023.
3. M.J. Hirsch, “A Not So Random Walk Through the World of Operations Research,” West Chester University Mathematics Department Colloquium, West Chester, PA. April 2023. YouTube Video.
4. M.J. Hirsch, “A Not So Random Walk Through the World of Operations Research,” Plenary lecture, University of North Florida Osprey Undergraduate Mathematics Conference, Jacksonville, FL. April 2023.
5. W. Trevena, A. Semenov, M.J. Hirsch, P.M. Pardalos, and I. Kotsireas, “Solving Large Systems of Nonlinear Equations with Global Optimization in the Cloud,” PanOptiC View on Global Optimization Workshop, Gainesville, FL. March 2023.

2022

1. M.J. Hirsch, “Optimization Everywhere: An overview of operations research and its connection to the real-world,” University of North Florida Department of Mathematics Colloquium Series, Jacksonville, FL. December 2022.
2. J. Mimbs, “Validating a Tsunami Model for Coastal Inundation,” Julia Conference, Virtual. July 2022.
3. P. Guilbaud, C. Sanders, M.J. Hirsch, and T.C. Guilbaud, “Social-Emotional Competence for the Greater Good: Exploring the Use of Serious Game, Virtual Reality, and Artificial Intelligence to Elicit Prosocial Behaviors and Strengthen Cognitive Abilities of Youth, Adolescents, and Educators – A Systematic Review,” Virtual, Augmented, and Mixed Reality: Design and Development, J.Y.C. Chen and G. Fragomeni (eds.), pp. 423–442, 2022.
4. P. Guilbaud and M.J. Hirsch, “Promoting Equity and Achievement in Real-time Learning (PEARL): Towards a Framework for the Formation, Creation, and Validation of Stackable Knowledge Units,” Adaptive Instructional Systems, R.A. Sottilare and J. Schwarz (eds.), pp. 159–173, 2022.
5. M.J. Hirsch, A. Schunk, H.J. Ortiz-Pena, and B. Smith, “Machine Learning and Operations Research to Minimize the Risk of Detection by Adversarial Assets,” Military Operations Research Society Symposium, Quantico, VA. June 2022.
6. M.J. Hirsch and J.A. Crowder, “Machine Learning to Augment the Fusion Process for Data Classification,” Explainable AI and Other Applications of Fuzzy Techniques – Lecture Notes in Networks and Systems, J. Rayz, V. Raskin, S. Dick, and V. Kreinovich (eds.), vol. 258, pp. 154 – 165, 2022.

2021

1. M.J. Hirsch and H.J. Ortiz-Pena, “Reducing Transmission Footprint while Maximizing Value of Information on Dynamic Communication Networks,” Military Operations Research Society Symposium, Virtual. June 2021.
2. S. Friess, J.A. Crowder, and M.J. Hirsch, “Synthetic AI Nervous/Limbic Derived Instances (SANDI),” Transactions on Computational Science and Computational Intelligence, H. Arabnia (ed.), pp. 477 – 490, 2021.

2020

1. M.J. Hirsch, “Situation Alignment for Distributed Operations,” IEEE Proc. of the Cognitive and Computational Aspects of Situation Management Conference, pp. 7 – 11, Victoria, BC, Canada. August 2020.
2. S.M. Al-Shehri, P. Loskot, and M.J. Hirsch, “Localization Enhanced Mobile Networks,” Mobile Computing, J.H. Ortiz (ed.), Intech Open, Ch. 5, 2020.
3. M.J. Hirsch, H.J. Ortiz-Pena, M. Worden, and D. Johnston, “Determination of Smart Nodes in a Temporal Communication Network to Maximize the Value of Data and Minimize the Risk of Detection to the Nodes in the Network,” Military Operations Research Society Symposium, New Groton, CT. June 2020.

2019

1. S.M. Al-Shehri, P. Loskot, and M.J. Hirsch, “Enabling Connectivity for Tactical Networks in Mountainous Areas by Aerial Relays,” Journal of Telecommunication Systems, vol. 71, no. 4, pp. 561 – 575, 2019.
2. M.J. Hirsch, H.J. Ortiz-Pena, M. Worden, and D. Johnston, “Real-Time Decentralized Strategies for Routing Information across Temporally Dynamic Communication Networks,” Military Operations Research Society Symposium, Colorado Springs, CO. June 2019.

2018

1. M.J. Hirsch and A. Sadeghnejad, “Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks,” Advances in Science, Technology, and Engineering Systems Journal, vol. 3, no. 4, pp. 327 – 340, 2018.
2. S.M. Al-Shehri, P. Loskot, and M.J. Hirsch, “Tutorial: Geolocation Enhanced Mobile Communication Networks,” Military Communications Conference, Los Angeles, CA. October 2018.

2017

1. M.J. Hirsch and H.J. Ortiz-Pena, “Information Supply Chain Optimization with Bandwidth Limitations,” International Transactions in Operational Research, vol. 24, no. 5, pp. 993 – 1022, 2017.
2. M.J. Hirsch and N. Navarro, “Risk Constraints for Portfolio Optimization with Fixed-Fee Transaction Cost,” Journal of Investment Strategies, vol. 6, no. 2, pp. 91 – 112, 2017.
3. F. Stefanello, L.S. Buriol, M.J. Hirsch, P.M. Pardalos, T. Querido, M.G.C. Resende, and M. Ritt, “On the Minimization of Traffic Congestion in Road Networks With Tolls,” Annals of Operations Research, vol. 249, no. 1, pp. 119 – 139, 2017.
4. M.J. Hirsch, A. Sadeghnejad, and H.J. Ortiz-Pena, “Shortest Paths for Routing Information over Temporally Dynamic Communication Networks,” IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD. October 2017.
5. M.J. Hirsch, A. Sadeghnejad, H.J. Ortiz-Pena, and M. Sudit, “Optimal Communication of Information for Warfighter Fire Control Benefit,” National Fire Control Symposium, Orlando, FL. February 2017.

2016

1. H.J. Ortiz-Pena, M.J. Hirsch, M. Karwan, and M. Sudit, “Routing of Cooperative Autonomous Vehicles for Persistent ISR,” National Fire Control Symposium, Orlando, FL. February 2016.
2. M.J. Hirsch, “On Variants of the Target Visitation Problem,” University of North Florida Department of Mathematics Colloquium Series, Jacksonville, FL. September 2016.

1. M.J. Hirsch, H. Ortiz-Pena, and C. Eck, “Cooperative Control of Unmanned Aerial Vehicles for Tracking Targets.’’ United States Patent 8,639,396. Issued on January 28, 2014. View Patent
2. M.J. Hirsch and J. Geiss, “Pattern Learning System – A Graph Theoretic Approach to Temporal Pattern Learning.” United States Patent 8,489,522. Issued on July 16, 2013. View Patent
3. M.J. Hirsch, D.M. Sudit, and R. Nagi, “Optimization Strategies for Resource Management and Course of Action Analysis.” United States Patent 8,199,643. Issued on June 12, 2012. View Patent
4. M.J. Hirsch, P.M. Pardalos, and M.G.C. Resende, “Sensor Registration by Global Optimization Procedures.” United States Patent 7,974,816. Issued on July 5, 2011. View Patent
5. M.J. Hirsch, P.M. Pardalos, and M.G.C. Resende, “Sensor Registration by Global Optimization.” United States Patent 7,653,513. Issued on January 26, 2010. View Patent