Ankit Shah

Assistant Professor,
Industrial and Management Systems Engineering
Director,
AIR Lab for Secure and Efficient Systems

University of South Florida

Biography

Ankit Shah is an Assistant Professor of Industrial and Management Systems Engineering at the University of South Florida (USF). He also holds appointments as Affiliate Assistant Professor in USF's Electrical Engineering and Computer Science and Engineering departments. Dr. Shah is the director of the Artificial Intelligence Research (AIR) Laboratory for Secure and Efficient Systems and a member of the USF Institute for Artificial Intelligence + X (AI+X). He is also a USF NSF I-Corps Fellow. Before joining USF, Dr. Shah was a researcher in the field of Reinforcement Learning at the Lawrence Livermore National Laboratory in CA and the Center for Secure Information Systems in VA. With over nine years of industry experience in the Information Technology and Security sector, he has held diverse positions, ranging from a software engineer to the executive role of Vice President.

Dr. Shah's research interests revolve around the convergence of Computer Science, Operations Research, Data Science, and Information Technology, with a strong focus on Artificial Intelligence for Cybersecurity. His methodological research is in deep reinforcement learning and adversarial machine learning for threat reduction and enhancing system security. His research sponsors are the Department of Defense (DoD), the Department of Homeland Security (DHS), and industry partners. Dr. Shah's work has been published in top journals, including ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Information Forensics and Security, ACM Transactions on Privacy and Security, IEEE Transactions on Services Computing, IEEE Transactions on Parallel and Distributed Systems, and IEEE Transactions on Dependable and Secure Computing, among others. His Erdős number is 3 and Dijkstra number is 4.

Dr. Shah has served in various capacities for both conferences and journals. He is an Organizing Committee Member for the 2024 INFORMS Conference on Security, coordinating the Data, Artificial Intelligence and Cyber track. He recently served as an Organizing Committee Member for the Workshop on Artificial Intelligence for Cyber Security (AICS) at the AAAI 2024 conference and a Program Committee Member for the International Joint Conference on Artificial Intelligence (IJCAI-24). He also served as the Workshop Chair for the IEEE Conference on Dependable and Secure Computing (IEEE DSC) 2023 and chaired the Cybersecurity Analytics session for the Military and Security Society at the INFORMS Annual Meeting 2023. Dr. Shah was the Cybersecurity Cluster Chair at the INFORMS Annual Meeting in 2020 and 2022. He also co-chaired the AI for Cybersecurity session at the 2022 INFORMS Annual Meeting, led the Data Analytics and Simulation session at the 2021 INFORMS Annual Meeting, and chaired the Simulation and Reinforcement Learning session at the 2021 INFORMS Annual Meeting. Furthermore, he served as a Program Committee Member for the IEEE International Conference on Intelligence and Security Informatics in 2020-2023, the 2021 ACM KDD Workshop on Artificial Intelligence-enabled Cybersecurity Analytics, and the IEEE ICDM Workshop on Deep Learning for Cyber Threat Intelligence in 2020. In 2019, Dr. Shah was invited as a Panelist at the AAAI Workshop on Artificial Intelligence for Cybersecurity. His expertise has led to invitations for numerous technical talks and seminars from government organizations, industry partners, and technical associations.

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Lawrence Brown

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