Ankit Shah is an Assistant Professor of Industrial and Management Systems Engineering. He 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. He has over nine years of industry experience in the Information Technology and Security sector. 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. He specializes in developing AI-enabled methods to aid human decision-making, addressing the identification and mitigation of digital and physical threats in defense and civilian domains. His research sponsors are the Department of Defense, the Department of Homeland Security, 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. He is a recipient of USF Research and Innovations Outstanding Research Achievement awards in 2022 and 2023, as well as Office of the Provosts Outstanding Undergraduate Teaching award for 2021-2022. Dr. Shah also holds the distinction of being a Senior Member of IEEE.