John Fossaceca, Ph.D.

Department: Cybersecurity, Artificial Intelligence & Machine Learning

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Dr. John M. Fossaceca currently serves as the Division Chief for the U.S. Army Research Laboratory’s Science of Intelligent Systems Division. In this role, he supports research programs in Artificial Intelligence and Machine Learning for autonomous systems, robotics, machine intelligence, multi-agent behaviors, and system adaptation. Before becoming the SISD Chief, Dr. Fossaceca held positions as the Program Manager for ARL’s Essential Research Program in AI for Maneuver & Mobility, and as Associate Chief for the Information Sciences Division at ARL. His prior roles illustrate his extensive experience and leadership in the field. Dr. Fossaceca has occupied senior positions in various industries. He served as VP for Technology at Ultra-3eTI, Executive VP of Engineering and COO of Comtech Mobile Datacom, and Director of Internetworking Systems at Bell Laboratories.

As Executive VP of Engineering at Comtech, Dr. Fossaceca managed the team responsible for the modernization of the U.S. Army’s satellite-based Blue Force tracking system. At 3eTI, Dr. Fossaceca held the role of VP of Engineering and also served as the Principal Investigator for Small Business Innovation Research programs with the U.S. Navy. This was during 3eTI’s start-up phase, where his team achieved a milestone by developing some of the first secure Wi-Fi technology accredited by the U.S. Government. Dr. Fossaceca was also an Engineering Director at AT&T/Lucent/Bell Labs for Next Generation Telecommunications Systems developing several consumer and telecom products including early VoIP telephony technology.

Dr. Fossaceca has conducted research and development in adaptive signal processing, machine learning, communications and cybersecurity. His present research interests are in online continuous machine learning in data-constrained environments, applications of Generative AI for embodied systems and resilient autonomy. Dr. Fossaceca is co-inventor on six patents related to wireless communications and signal detection, and he serves as a reviewer for several refereed journals. He teaches graduate courses in Artificial Intelligence, Machine Learning, Cryptography, Intrusion Detection, and Cybersecurity, and serves as a Ph.D. research advisor for several students.

Dr. Fossaceca's educational background includes a bachelor’s degree in electrical engineering from Manhattan College and a master’s degree in the same field from Syracuse University. He also holds an M.B.A. from Virginia Tech and completed his Ph.D. in systems engineering at George Washington University.

Publications

“Strategic maneuver and disruption with reinforcement learning approaches for multi-agent coordination.” Asher, D. E., Basak, A., Fernandez, R., Sharma, P. K., Zaroukian, E. G., Hsu, C. D., ... & Fossaceca, J. (2023). The Journal of Defense Modeling and Simulation, 20(4), 509-526.
"Delivering on the promise of autonomous agents in the battlefield." Fossaceca, John M. Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V 12538 (2023): 310-319.
"A cloud-based computing framework for artificial intelligence innovation in support of multidomain operations." Robertson, James, John M. Fossaceca, and Kelly W. Bennett. IEEE Transactions on Engineering Management 69, no. 6 (2021): 3913-3922.
MARK-ELM: Application of a novel Multiple Kernel Learning framework for improving the robustness of Network Intrusion Detection JM Fossaceca, TA Mazzuchi, S Sarkani Expert Systems with Applications 42 (8), 4062-4080
A semi-boosted nested model with sensitivity-based weighted binarization for multi-domain network intrusion detection JW Mikhail, JM Fossaceca, R Iammartino ACM Transactions on Intelligent Systems and Technology (TIST) 10 (3), 1-27
Artificial Intelligence and Machine Learning for Future Army Applications JM Fossaceca, SH Young Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX. Vol. 10635. International Society for Optics and Photonics, 2018
Multi-attribute Framework for Requirements Elicitation in Phased Array Radar Systems M Tompkins, R Iammartino, J Fossaceca IEEE Transactions on Engineering Management
Evaluation of preconditions affecting symptomatic human error in general aviation and air carrier aviation accidents AJ Erjavac, R Iammartino, JM Fossaceca Reliability Engineering & System Safety 178, 156-163
Software obsolescence risk assessment approach using multicriteria decision‐making TF Bowlds, JM Fossaceca, R Iammartino Systems Engineering 21 (5), 455-465
Assessing the impact of requirements review on quality outcomes TE White, R Iammartino, JM Fossaceca Quality and Reliability Engineering International 34 (5), 882-893