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Houbing Herbert Song

Profile photo for Houbing Herbert Song

Professor

Information Systems
Computer Science and Electrical Engineering

Information Technology & Engineering 427

Education

Ph D University of Virginia 2012

MS University of Texas at El Paso 2006

About

Houbing Herbert Song is a Professor in the department of Information Systems at UMBC, where he directs the Security and Optimization for Networked Globe Laboratory (SONG Lab). He received his Ph.D. in Electrical Engineering from the University of Virginia in 2012. His research focuses on neuro-symbolic AI, anomaly detection, Artificial Intelligence of Things (AIoT), autonomous systems, and cyber-physical systems, with support from federal agencies and industry. Dr. Song is an IEEE Fellow, ACM Distinguished Member, elected Member of the European Academy of Engineering (EAE), and a Web of Science Highly Cited Researcher. He has authored more than 500 articles, edited more than 10 books, and holds two patents. He serves as Co-Editor-in-Chief of IEEE Transactions on Industrial Informatics and holds editorial and leadership roles across major IEEE and ACM communities, including the Founding Chair of the ACM Emerging Interest Group on Trustworthy and Responsible Systems (EIGTRUST). He is also an ACM Distinguished Speaker and IEEE Distinguished Lecturer/Visitor across multiple societies, including SYSC, CIS, CS, ComSoc, ITSS, and VTS, and has received numerous honors, including the IEEE Harry Rowe Mimno Award, the Research.com Rising Star of Science Award, and more than 10 Best Paper Awards.

Research Interests

Neuro-symbolic AI; Trustworthy Systems; Anomaly Detection; Artificial Intelligence of Things

Teaching Interests

AI/Machine Learning, Computer Networks

Contracts, Fellowships, Grants, and Sponsored Research

Gaur, Manas (Co-Principal), Song, Houbing (Principal). “Collaborative Research: VINES: Track 1: NSF-JST: Neuro-symbolic AI-Native Design of Semantic Communications,” Grant (Currently Under Review). Sponsored By: NSF.

Lu, Ye, Song, Houbing. “Physics-constrained machine learning-enabled efficient grain growth modeling for 3D printed metals,” Grant Sponsored By: COEIT.

Intellectual Contributions

Li, David, Song, Houbing. (2025). . 2025 International Wireless Communications and Mobile Computing (IWCMC) IEEE.

Renkhoff, Justus, Feng, Ke, Meier-Doernberg, Marc, Velasquez, Alvaro, Song, Houbing Herbert. (2024). A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence. 8. 5 15 IEEE Transactions on Artificial Intelligence.

Adil, Muhammad, Menon, Varun, Balasubramanian, Venki, Alotaibi, Sattam, Song, Houbing, Jin, Zhanpeng, Farouk, Ahmed. . IEEE Sensors Journal.