Md Shirajum Munir is currently working as an Assistant Professor of Computer Science, at the School of Computing, Analytics, and Modeling, University of West Georgia, Carrollton, GA, USA.  Previously, he worked as a Research Assistant Professor in the School of Cybersecurity, at Old Dominion University, USA from July 2023 to August 2024, and performed the role of a Visiting Faculty at the Air Force Research Lab (AFRL), Rome, NY, USA from May 2024 to July 2024.  He served as a Post-doctoral Research Associate from September 2022 to July 2023 at Virginia Modeling, Analysis, and Simulation Center, Old Dominion University, USA.  He also served as a Postdoctoral Researcher from September 2021 to August 2022 with the Department of Computer Science and Engineering, Kyung Hee University (KHU), South Korea. He received the B.S. degree in Computer Science and Engineering from Khulna University, Khulna, Bangladesh, in 2010, and the Ph.D. degree in Computer Engineering from Kyung Hee University (KHU), South Korea, in 2021. Before his Ph.D., he served as a Software Engineer, Senior Software Engineer, and Lead Engineer with the Solution Laboratory, Samsung Research and Development Institute, Dhaka, Bangladesh, from 2010 to 2016. He is serving as an associate editor of the IEEE Internet of Things Journal since April 2023. He is a member of IEEE, IEEE Communication Society, and IEEE Young Professional.  His research interests include machine learning, data science, trustworthy artificial intelligence and stochastic models for wireless network resource management, sustainable edge computing, healthcare, industrial IoT, intelligent IoT network management, future internet, and resilient smart grid. 

Md Shirajum Munir is a multidisciplinary researcher, his research focuses on intelligent cyber-physical systems, cyber-security and risk, energy economics, renewable energy management, the Internet of Things systems, sustainable edge computing, wireless communication, intelligent healthcare and well-being systems, and resilient smart grid operation through developing data-informed artificial intelligence and stochastic models. 14+ years’ research and development experience in industry and academia as a Computer Engineer professional. Specifically, research on developing domain-specific, trustworthy, and explainable artificial intelligence mechanisms through investigating, modeling, and capturing data uncertainty of complex cyber-physical systems. He is an expert on stochastic games, reinforcement learning (RL), risk-adversarial learning, multi-agent/meta-RL, trustworthy AI, generative AI, stochastic optimization, data science, and dynamic programming.