ECE Department Seminar
Networked Systems and Security Research
in the Age of AI/Machine Learning
Houbing Song, Ph.D.
Department of Electrical Engineering and Computer Science
Embry-Riddle Aeronautical University
Wednesday, February 24, 2021
10:00 am – 11:00 am
Zoom Meeting Link:
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. Finally I will present my research plan, and identify potential collaborators and funding opportunities.
Bio: Houbing Song received the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in August 2012. In August 2017, he joined the Department of Electrical Engineering and Computer Science, Embry-Riddle Aeronautical
University, Daytona Beach, FL, where he is currently an Assistant Professor and the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab, www.SONGLab.us). He is supervising 7 Ph.D. students with 2 expected to graduate in May 2021
(each has been selected as a finalist for at least 2 tenure-track assistant professor positions). He has served as an Associate Technical Editor for IEEE Communications Magazine (2017-present), an Associate Editor for IEEE Internet of Things Journal (2020-present)
and IEEE Journal on Miniaturization for Air and Space Systems (J-MASS) (2020-present). He is the editor of 8 books, including Cyber-Physical Systems, Academic Press, 2016; Big Data Analytics for Cyber-Physical Systems: Machine Learning for the Internet of
Things, Elsevier, 2019; Smart Cities, Wiley, 2017; Smart Transportation: AI Enabled Mobility and Autonomous Driving, CRC Press, 2021; Industrial Internet of Things, Springer, 2016, and Security and Privacy in Cyber-Physical
Systems, Wiley-IEEE Press, 2017. He is the author of more than 200 articles (Number of Google Citations: 11,600+; Google h-index: 52). His research interests include AI/machine learning/big data analytics, cyber-physical
systems/internet of things, unmanned aircraft systems, cybersecurity and privacy, and wireless communications and networking. His research has been supported by federal agencies (including US Department of Transportation, National Science Foundation, Federal
Aviation Administration, US Department of Defense-Army, and Air Force Research Laboratory) and industry. His research has been featured by popular news media outlets, including IEEE GlobalSpec's Engineering360, Security Magazine, Association for Unmanned Vehicle
Systems International (AUVSI), Fox News, U.S. News & World Report, The Washington Times, Battle Space and Defense Daily. Dr. Song is a senior member of both IEEE and ACM, and an ACM Distinguished Speaker. He received 5 Best Paper Awards (IEEE CPSCom-2019,
IEEE ICII 2019, IEEE/AIAA ICNS 2019, IEEE CBDCom 2020, and WASA 2020).