Professor Song

Abstract: Networked systems have created new opportunities with major societal implications. At the same time, security has emerged as one of the most important socio-technical challenges confronting society. AI/machine learning (ML) techniques are expected to enable networked systems and enhance security. In this talk, I will present my recent research on networked systems and security in the age of AI/ML. First, I will introduce my ML-enabled Counter Unmanned Aircraft System(s) (C-UAS) technology that detects and safely neutralizes rogue drones without destroying them or causing them to crash. This research has been featured by 100+ news media outlets. Next I will present my follow-up research on real-time ML for quickest event (threat/intrusion/vulnerability…) detection. Then I will introduce my research on data-efficient ML, particularly distant domain transfer learning.

Biography:

Houbing Herbert Song (M’12–SM’14-F’23) received the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in August 2012. He is currently a Professor, the Founding Director of the NSF Center for Aviation Big Data Analytics (Planning), the Associate Director for Leadership of the DOT Transportation Cybersecurity Center for Advanced Research and Education (Tier 1 Center), and the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab, www.SONGLab.us), University of Maryland, Baltimore County (UMBC), Baltimore, MD. He is a Distinguished Visiting Fellow of the Scottish Informatics and Computer Science Alliance (SICSA). Prior to joining UMBC, he was a Tenured Associate Professor of Electrical Engineering and Computer Science at Embry-Riddle Aeronautical University, Daytona Beach, FL. He serves as an Associate Editor for IEEE Transactions on Artificial Intelligence (TAI) (2023-present), IEEE Internet of Things Journal (2020-present), IEEE Transactions on Intelligent Transportation Systems (2021-present), and IEEE Journal on Miniaturization for Air and Space Systems (J-MASS) (2020-present). He was an Associate Technical Editor for IEEE Communications Magazine (2017-2020). He is the editor of ten books, the author of more than 100 articles and the inventor of 2 patents. His research interests include AI/machine learning/big data analytics, cyber-physical systems/internet of things, and cybersecurity and privacy. His research has been sponsored by federal agencies (including National Science Foundation, National Aeronautics and Space Administration, US Department of Transportation, and Federal Aviation Administration, among others) and industry. His research has been featured on popular news media outlets, including IEEE Spectrum, IEEE GlobalSpec's Engineering360, IEEE Transmitter, insideBIGDATA, Association for Uncrewed Vehicle Systems International (AUVSI), Security Magazine, CXOTech Magazine, Fox News, U.S. News & World Report, The Washington Times, and New Atlas.  

Dr. Song is an IEEE Fellow, an Asia-Pacific Artificial Intelligence Association (AAIA) Fellow, an ACM Distinguished Member, and a Full Member of Sigma Xi. Dr. Song has been a Highly Cited Researcher identified by Web of Science since 2021. He is an ACM Distinguished Speaker (2020-present), an IEEE Computer Society Distinguished Visitor (2024-present), an IEEE Communications Society (ComSoc) Distinguished Lecturer (2024-present), an IEEE Intelligent Transportation Systems Society (ITSS) Distinguished Lecturer (2024-present), an IEEE Vehicular Technology Society (VTS) Distinguished Lecturer (2023-present) and an IEEE Systems Council Distinguished Lecturer (2023-present). Dr. Song received Research.com Rising Star of Science Award in 2022, 2021 Harry Rowe Mimno Award bestowed by IEEE Aerospace and Electronic Systems Society, and 10+ Best Paper Awards from major international conferences, including IEEE CPSCom-2019, IEEE ICII 2019, IEEE/AIAA ICNS 2019, IEEE CBDCom 2020, WASA 2020, AIAA/ IEEE DASC 2021, IEEE GLOBECOM 2021 and IEEE INFOCOM 2022. He has been an IEEE Impact Creator since 2023. 

Email:

Address:Department of Information Systems, University of Maryland, Baltimore, United States, MD 21250