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The Brookhaven AI/ML Seminar (AIMS) series is about showcasing research at Brookhaven National Laboratory (BNL) and elsewhere that uses AI and Machine Learning to enhance scientific discovery and that uses domain science questions to motivate new AI developments.
Abstract: There has been an increasing desire to push artificial intelligence (AI) frontiers to the network edge to utilize the enormous amount of data generated by the Internet of things (IoT) and/or edge devices nearer to the data source. This desire has led to the merger of edge computing and AI, resulting in a new paradigm—AI at the edge or edge intelligence. Intelligent edge computing systems have applications in numerous domains including but not limited to space, sports, agriculture, defense, health care, and autonomous vehicles. However, edge devices are susceptible to electronic failures and security attacks. Further, safety and security risks of edge computing systems increase with the degree of AI-enabled autonomy, which require safety and security to be integrated in the design of intelligent edge computing systems. In this seminar, the speaker presents a perspective that hardware/software co-design is imperative in order to design secure and intelligent edge computing systems that adhere to edge applications' timeliness and energy constraints.
Bio: Dr. Arslan Munir is currently an Associate Professor in the Department of Computer Science (CS) at Kansas State University (K-State). He is a founding director of the Intelligent Systems, Computer Architecture, Analytics, and Security (ISCAAS) laboratory at K-State. He was a postdoctoral research associate in the Electrical and Computer Engineering (ECE) department at Rice University, Houston, Texas, USA from May 2012 to June 2014. He received his M.A.Sc. in ECE from the University of British Columbia, Vancouver, Canada, in 2007 and his Ph.D. in ECE from the University of Florida, Gainesville, Florida, USA, in 2012. From 2007 to 2008, he worked as a software development engineer at Mentor Graphics in the Embedded Systems Division.
Dr. Munir's current research interests include embedded and cyber-physical systems, secure and trustworthy systems, computer architecture, AI, computer vision, parallel computing, and quantum computing. He received many academic awards including the doctoral fellowship from Natural Sciences and Engineering Research Council (NSERC) of Canada, gold medals for best performance in electrical engineering, and gold medals and academic roll of honor for securing rank one in pre-engineering examinations. He has published more than 90 scholarly peer- reviewed articles related to his research interests with three of his research papers receiving Best Paper Awards and two more being selected as Best Paper Finalists. His research accomplishments have been covered by various news and media outlets.
His research has been sponsored by the National Science Foundation (NSF), Air Force Office of Scientific Research (AFOSR), Air Force Research Laboratory (AFRL), National Aeronautics and Space Administration (NASA), and Semiconductor Research Corporation (SRC). He has been awarded the NSF Computer and Information Science and Engineering Research Initiation Initiative award. He has also been awarded Summer Faculty Fellowships at AFRL, Information Directorate (RI) in 2019, 2020, 2021, and 2023. He currently serves as an associate editor and guest editor for various journals including AI, Journal of Imaging, Entropy, and Journal of Cybersecurity and Privacy. He also served as an Associate Editor for IEEE Consumer Electronics Magazine. He is a Senior Member of IEEE.