Talk: The Third Wave of Artificial Intelligence: Neurosymbolic AI
ACM Distinguished Speaker: Prof. Houbing Song (ACM website; UMBC CSEE page; SONG Lab)
Time: Nov. 25th, 2025, Tuesday, 11:15am to 12:45pm
Location: UMBC ITE 325b
Abstract
There are three waves of Artificial Intelligence. The first Wave of AI is Crafted Knowledge, which includes rule-based AI systems. The second wave of AI is Statistical Learning, which includes machine becoming intelligent by using statistical methods. The third wave of AI is contextual adaptation. In the third wave, instead of learning from data, intelligent machines will understand and perceive the world on its own, and learn by understanding the world and reason with it. Neurosymbolic AI, which combines neural networks with symbolic representations, has emerged as a promising solution of the third wave of AI. In this talk, I will my perspective on the emerging area.
Bio:
Houbing 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 Tenured Associate Professor, the Director of NSF Center for Aviation Big Data Analytics (Planning), 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. 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 eight books, the author of more than 100 articles and the inventor of 2 patents. His research interests include cyber-physical systems/internet of things, cybersecurity and privacy, and AI/machine learning/big data analytics. His research has been sponsored by federal agencies (including National Science Foundation, US Department of Transportation, and Federal Aviation Administration, among others) and industry. His research has been featured by popular news media outlets, including IEEE GlobalSpec’s Engineering360, 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 ACM Distinguished Member, and an ACM Distinguished Speaker. Dr. Song has been a Highly Cited Researcher identified by Clarivate™ (2021, 2022) and a Top 1000 Computer Scientist identified by Research.com. He received Research.com Rising Star of Science Award in 2022 (World Ranking: 82; US Ranking: 16). Dr. Song was a recipient of 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.
