Houbing Herbert Song is a Chinese‑American electrical engineer and computer scientist specializing in cyber‑physical systems, big data analytics, and the integration of artificial intelligence with the Internet of Things. He is a tenured associate professor in the Department of Electrical, Computer, Software, and Systems Engineering at the University of Maryland, Baltimore County (UMBC).
Education
Song earned his Ph.D. in Electrical Engineering from the University of Virginia in August 2012.
Academic and Research Roles
At UMBC, Song serves as the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab). He is also the Co‑Editor‑in‑Chief of the IEEE Transactions on Industrial Informatics. Since 2021, he has been recognized as a Highly Cited Researcher by Clarivate/Web of Science, reflecting the significant impact of his publications, which have amassed over 41 000 citations and an h‑index of 100.
Professional Honors
- IEEE Fellow (2022) for contributions to big data analytics and AI‑IoT integration.
- Distinguished Member of the Association for Computing Machinery (ACM) (2022).
- Founding Chair of the IEEE Internet of Things (IoT) Technical Community’s TRUST‑IoT Working Group (2024).
- Founding Chair of the ACM Emerging Interest Group on Trustworthy and Responsible Systems (EIGTRUST) (2025).
- Fellow of the Asia‑Pacific Artificial Intelligence Association and the International Artificial Intelligence Industry Alliance.
- Member of the National Academy of Artificial Intelligence.
- Multiple Highly Cited Researcher recognitions (2021‑2023) in Computer Science and Cross‑Field categories.
- Recipient of numerous awards, including the IEEE Aerospace and Electronic Systems Society Distinguished Speaker award and the Research.com Rising Star of Science award.
Research Focus
Song’s research addresses the security, reliability, and optimization of large‑scale networked systems, particularly in transportation and aviation domains. He leads initiatives within NSF‑funded centers, including the Center for Aviation Big Data Analytics and the DOT Transportation Cybersecurity Center for Advanced Research.
Publications and Impact
He has authored extensively in journals and conference proceedings, contributing to the development of trustworthy AI, data‑driven transportation systems, and cyber‑physical infrastructure. His work is frequently cited in both academic literature and industry standards.
All information presented is derived from publicly available sources, including the subject’s Wikipedia entry and institutional biographies.
