Abbas Yazdinejad, Ph.D., is an Assistant Professor in the Department of Computer Science at the University of Regina and the Director of the Decentralized Cybersecurity & Artificial Intelligence Lab (DCAILab). He has been recognized among the World’s Top 2% Scientists (Stanford University ranking). His research focuses on artificial intelligence and machine learning for critical, safety- and security-sensitive applications, with particular emphasis on agentic AI systems, large language model (LLM) security and governance, autonomous cybersecurity, privacy-preserving machine learning, federated learning, Internet of Things (IoT) and Industrial IoT, and quantum computing. He has held postdoctoral research positions at the University of Toronto and the University of Guelph. His work bridges technical innovation, teaching, and industry-engaged research to advance trustworthy and resilient digital systems.
Abbas Yazdinejad
Balsillie Scholar Assistant Professor in Cybersecurity, Department of Computer Science University of Regina
Balsillie Scholar
Balsillie Scholar
January - August 2026
January - August 2026
RESEARCH CLUSTER
RESEARCH CLUSTER
Abbas Yazdinejad
Balsillie Scholar
Assistant Professor in Cybersecurity, Department of Computer Science University of Regina
Awards
- Recognized among the World’s Top 2% of Scientists in the Stanford University ranking for contributions to Artificial Intelligence & Image Processing, Networking & Telecommunications, and Information & Communication Technologies (2022–2025).
Select Publications
- Robust Privacy-Preserving Federated Learning Model Against Model Poisoning Attacks
- An Explainable and Privacy-Preserving Federated Learning Model for Threat Detection in Cyber-Physical-Social Systems
- Responsible Use of Large Language Models in Digital Health: An Equity First Governance Framework
- A Community-Centred Protocol for Ethical and Scalable AI in Health Care
- Breaking Interprovincial Data Silos: How Federated Learning Can Unlock Canada’s Public Health Potential
- Hybrid privacy preserving federated learning against irregular users in next-generation Internet of Things
- AP2FL: Auditable privacy-preserving federated learning framework for electronics in healthcare
- Secure Intelligent Fuzzy Blockchain Framework: Effective Threat Detection in IoT Networks
- Block Hunter: Federated Learning for Cyber Threat Hunting in Blockchain-based IIoT Networks
- Autonomous Cybersecurity: Evolving Challenges, Emerging Opportunities, and Future Research Trajectories
Education
- Postdoctoral Scholar, Artificial Intelligence and Mathematical Modeling Lab (AIMMlab); University of Toronto, Toronto, ON, Canada – January 2025 – December 2025
- Postdoctoral Scholar, Cyber Science Lab (CSL), Canada Cyber Foundry; University of Guelph, Guelph, ON, Canada – January 2024 – December 2024
- Ph.D. in Computational Sciences – Cybersecurity; University of Guelph, Guelph, ON, Canada – 2024