Shen-Shyang Ho

Shen-Shyang Ho is a Full Professor in the Department of Computer Science at Rowan University's College of Science & Mathematics. His work spans machine learning, data mining, and edge computing with applications in urban mobility, precision agriculture, and data privacy. He leads NSF-funded research projects on dynamic graph analysis and spatiotemporal anomaly detection.

• Ph.D. in Computer Science, George Mason University
• Post-Doctoral Associate, Caltech & NASA JPL
• B.S. in Mathematics with Computational Science, National University of Singapore

Research expertise includes graph-based machine learning, conformal prediction, cooperative inference, and privacy-preserving ML. Current work focuses on federated learning for edge devices and anomaly detection in evolving systems. He has developed tools like SplitTracer for cooperative inference evaluation and ParkGauge for urban mobility monitoring.

Recent publications highlight his contributions to 2026 Pattern Recognition journal (martingale-based graph analysis), 2025 IEEE ICAIC conference (blockchain gas optimization), and 2024 ACM SAC symposium (shared mobility systems). His work integrates machine learning with real-world constraints across energy grids, transportation, and agricultural technology.

• NSF Grant (2022) for Dynamic Graph Anomaly Detection
• NSF Grant (2018) for Spatiotemporal Analysis
• Google Scholar Classic Paper Recognition (2017) for 2006 Radar Micro-Doppler Study

Professional memberships include the Association for Computing Machinery (ACM). His teaching portfolio ranges from introductory programming to advanced ML courses. He previously held positions at Nanyang Technological University before joining Rowan in 2016.