Shen-Shyang Ho, Ph.D.
Shen-Shyang Ho, Ph.D.
Shen-Shyang Ho, Ph.D.
Full Professor
Biography
Websites: 
Lab WebsiteResearch with Rowan
Education:
Post-Doctoral Associate, California Institute of Technology and NASA Jet Propulsion Laboratory
Ph.D., Computer Science, George Mason University
B.S., Mathematics with Computational Science, National University of Singapore
Research Expertise:
Machine Learning | Data Mining | Artificial Intelligence | Pattern Recognition | Uncertainty Quantification | Data Privacy Issues
His recent research include graph-based machine learning tasks (forecasting, uncertainty quantification, change detection, anomaly detection, and their practical applications), conformal prediction and its applications, cooperative inference and its applications (e.g., precision agriculture, etc.), and privacy issues in machine learning techniques.
Teaching Narrative:
He has taught courses ranging from undergraduate freshmen courses such as introduction to object oriented programming to advanced graduate computer science courses in data mining, machine learning, artificial intelligence, etc.
Professional Memberships:
Association for Computing Machinery
Selected Publications:
Shen-Shyang Ho and Tarun Teja Kairamkonda. Change Point Detection in Evolving Graph using Martingale. In Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (SAC '24).
Lahari Voleti and Shen Shyang Ho. Personalized Learning with Limited Data on Edge Devices using Federated Learning and Meta-Learning. In Proceedings of the Eighth ACM/IEEE Symposium on Edge Computing (SEC '23).
Nicholas Bovee, Stephen Piccolo, Shen Shyang Ho, and Ning Wang. Experimental test-bed for Computation Offloading for Cooperative Inference on Edge Devices. In Proceedings of the Eighth ACM/IEEE Symposium on Edge Computing (SEC '23).
Dylan Perry, Ning Wang and S. -S. Ho, "Energy Demand Prediction with Optimized Clustering-Based Federated Learning," 2021 IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, 2021, pp. 1-6
