Dr. Saeed Samet

• Post Doctoral Fellow (2010 – 2012): E-Health Information Laboratory, Research Institute at the Children Hospital of Eastern Ontario (CHEO), Ottawa, ON, Canada
• Ph.D. in Computer Science (2010), University of Ottawa, Ottawa, ON, Canada
• M.Sc. in Computer Science (2005), McMaster University, Hamilton, ON, Canada
• M.Sc. in Computer Science (2003), Tehran University, Tehran, Iran

Research Interests:

• Privacy-Preserving in Data Mining, Machine Learning, and Statistics, Big Data, Social Networks
• e-Health Security and Privacy
• Health Informatics
• mHealth
• Cryptography and Network Security
• Secure Multi-party Computation
• Secret Sharing

Selected Publications:

Selected Publications

• A. Abdul Sattar Shaikh and S. Samet, Federated Graph Neural Networks In Non-IID Scenarios - A Comprehensive Survey. Published in Neurocomputing Journal, Volume 652, Pages: 44-54. DOI:, November 2025.


• M. E. Akhavanpour and S. Samet, Adaptive Model Selection in Stock Market Prediction: A Modular and Scalable Big Data Analytics Approach. International Journal of Computer Theory and Engineering (IJCTE). May 2024 Vol. 16(2). Pages: 44-54. DOI: 10.7763/IJCTE.2024.V16.1353.


• L. Bhatia and S. Samet, A Decentralized Data Evaluation Framework in Federated Learning. Journal of Blockchain: Research and Applications. In Press. July 2023. https://doi.org/10.1016/j.bcra.2023.100152.


• M. D. Firoozjaei, S. Samet, and A. A. Ghorbani, Parent Process Termination: An Adversarial Technique for Persistent Malware. Journal of Cyber Security Technology. August 2023. https://doi.org/10.1080/23742917.2023.2246229.


• F. Behnaminia and S. Samet, Blockchain Technology Applications in Patient Tracking Systems Regarding Privacy-Preserving Concerns and COVID-19 Pandemic. International Journal of Information and Communication Engineering. Volume 17, Issue 2. Pages 144-156. 2023.


• S. Zanbaghi and S. Samet, A Blockchain-Based Privacy-Preserving Physical Delivery System. International Journal of Information and Communication Engineering, Volume 16, Issue 11. Pages 532-539. 2022.
• S. Ziaeinejad and S. Samet, Context-Aware Client Selection in Federated Learning for Heterogeneous Medical Imaging. Accepted at the 10th International Conference on Medical and Health Informatics (ICMHI 2026), Kyoto, Japan, May 15-17, 2026.


• S. Ratnaparkhi and S. Samet, Fine-tuning Large-Language-Models using Federated Learning & Blockchain. Accepted at the LLMs, Big Data, and Multilinguality for All (LLMs4All) workshop at the IEEE Big Data 2025, Macau SAR, China, December 8-11, 2025.


• S. G. Grandhi and S. Samet, Evaluating the Long-Term Viability of Eye-Tracking for Continuous Authentication in Virtual Reality. Accepted at the 12th International Conference on Computer Networks & Communications (CCNET 2025), February 2025.


• K. Tahayori, S. Saad, M. Mamunand, and S. Samet, HybridMTD: Enhancing Robustness Against Adversarial Attacks with Ensemble Neural Networks and Moving Target Defense, Accepted at the 11th International Conference on Information Systems Security and Privacy (ICISSP 2025), February 2025.


• H. Hedayati and S. Samet, DataInsight: Big Data Analytics Services, Accepted in the 2024 IEEE International Conference on Big Data. December 2024. Washington DC, USA.


• M. V. Nezafat and S. Samet, Fake News Detection with Retrieval Augmented Generative Artificial Intelligence, The 2nd International Conference on Foundation and Large Language Models (FLLM 2024), Dubai, United Arab Emirates, November 2024, pp. 160-167, Doi: 10.1109/FLLM63129.2024.10852474.


• K. Tahayori, S. Saad, M. Mamunand, and S. Samet, Feasibility of Adversarial Attacks Against Machine Learning Models, Accepted in the International Conference on Wireless Intelligent, and Distributed Environment for Communication (WIDECOM) 2024. October 2024. 


• I. Aloran and S. Samet, A Secure Federated Learning Approach: Preventing Model Poisoning Attacks via Optimal Clustering, Accepted in the 7th International Conference on Data Science and Its Applications (ICoDSA) 2024. July 2024. Bali, Indonesia.


• I. Aloran and S. Samet, Defending Federated Learning Against Model Poisoning Attacks, IEEE Big Data 2023. Pages 3584-3589. December 2023. Sorrento, Italy.


• P. Shukla and S. Samet, RNBFT: Leveraging Randomness to Achieve Scalable Byzantine Consensus, IEEE Big Data 2023. Pages 2346-2355. December 2023. Sorrento, Italy.


• F. Behnaminia and S. Samet, Cross-Blockchain Technology for an Interoperable and Scalable Digital Contact Tracing, 12th International Conference on Software Engineering and Applications (SEAS 2023). Pages 79-94. September 2023. Toronto, Canada.


• S. Miri Rostami, S. Samet, and Z. Kobti, Objective-aware Reputation-enabled Blockchain-based Federated Learning, 4th International Congress on Blockchain and Applications. Pages 259-268. January 2023.


• S. Ziaeinejad, S. Samet, H. Fani, SEERa: A Framework for Community Prediction, Proceedings of the 31st ACM International Conference on Information & Knowledge Management(CIKM22). Pages 4762–4766. October 2022, Atlanta, Georgia, United States.


• L. Bhatia and S. Samet, Decentralized Federated Learning: A Comprehensive Survey and a New Blockchain-based Data Evaluation Scheme. The Fourth International Conference on Blockchain Computing and Applications (BCCA 2022), September 2022, San Antonio, Texas, United States.

Website: http://ssamet.myweb.cs.uwindsor.ca/

Meet Dr. Samet!