Mustafa Umut Ozbek
PhD Researcher in Nuclear Cybersecurity | Nuclear Engineer | AI for Critical Infrastructure
Graduate Research and Teaching Assistant at Ontario Tech University. He has been working on AI-driven OT cybersecurity (I&C) for nuclear power plants and other critical infrastructure. Mustafa has completed the master's degree in Energy and Power Engineering/Nuclear Engineering and Management at Tsinghua University. He is honored to have received the Best Thesis Performance and Best Academic Performance awards during his study. His research focuses on enhancing the safety and cybersecurity of nuclear power plants using machine learning and deep learning algorithms. Mustafa has been selected as an official member of the Delegation for the Future and has presented his work at the ICONS2024 in Vienna.
Research Areas - Nuclear Cybersecurity, OT/ICS Security, Reactor Simulation
His research brings together nuclear engineering, nuclear cybersecurity, OT/ICS/I&C systems security, SCADA security, reactor modeling and simulation, industrial cybersecurity, and artificial intelligence (machine learning, deep learning, explainable AI) to support safer and more resilient critical infrastructure systems.
Reactor Modeling & Simulation
Developing simulation-based models to analyze reactor behavior, system performance, and operational resilience.
Nuclear I&C Systems
Exploring the safety, reliability, and security of instrumentation and control systems in nuclear environments.
OT / ICS Cybersecurity
Strengthening industrial control systems through monitoring, risk assessment, and abnormal-behavior detection.
Machine Learning and Deep Learning
Using advanced AI techniques to reveal hidden patterns, detect anomalies, and improve engineering insight.
Research
Core research areas in nuclear engineering, AI, cybersecurity, and critical infrastructure.
Read More
Selected Work - Nuclear Security Research
Selected research themes and academic contributions spanning nuclear power plant cybersecurity, OT/ICS/I&C systems security, SCADA protection, reactor modeling and simulation, AI-enabled monitoring, anomaly detection, explainable AI, and cyber-aware engineering analysis for critical infrastructure.
AI-Driven Cybersecurity for Nuclear Power Plants
Research on enhancing the safety and cybersecurity of nuclear power plants using machine learning and deep learning algorithms.
Explainable AI for NPP I&C Anomaly Detection
Investigation of explainable AI methods to detect anomalies in nuclear instrumentation and control systems and improve interpretability in safety-relevant environments.
AI for Critical Infrastructure Monitoring
Development of intelligent monitoring perspectives for critical infrastructure environments where safety, reliability, and cyber resilience intersect.
Reactor-Oriented Modeling and Cyber-Aware Analysis
Research connecting reactor modeling, engineering simulation, and secure analytical frameworks for complex energy systems.
Selected Publications & Talks - IAEA, ICONS 2024
Peer-reviewed academic publications, IAEA ICONS 2024 presentations, and international technical contributions spanning nuclear power plant cybersecurity, OT/ICS/I&C systems security, explainable artificial intelligence (XAI), anomaly detection, machine learning, deep learning, reactor safety, and critical infrastructure resilience.
Li, J., & Ozbek, M.U. (2024). Enhancing Computer Security of NPPs Using Explainable AI. IAEA ICONS 2024, Vienna.
Li, J., Ozbek, M.U., & Li, B. Using Explainable AI to Detect Anomalies in I&C Systems of NPPs. SSRN.
IAEA CRP J02017: Enhancing Computer Security for Radiation Detection Systems (Contributor).
Experience & Education
Academic training and professional experience across cybersecurity, nuclear engineering, and critical infrastructure contexts.
PhD in Cybersecurity — Ontario Tech University, Canada
Research & Teaching Assistant
Jan 2026 – Present
Research focused on AI-driven cybersecurity for critical infrastructure, with emphasis on the safety and cybersecurity of nuclear power systems.
M.Sc. in Nuclear Engineering and Management — Tsinghua University, China
Sep 2022 – Jun 2024
GPA: 3.92/4.0. Thesis focused on enhancing the safety and cybersecurity of nuclear power plants using machine learning and deep learning algorithms.
B.Sc. in Mechanical Engineering — Dokuz Eylul University, Türkiye
2016 – 2021
Undergraduate training in engineering, supported by additional industrial engineering studies.
Professional Engineering and Research Experience
Experience spanning research, technical coordination, and data-driven work in demanding engineering environments connected to large-scale nuclear and critical infrastructure contexts.
International Engagement
His work also includes international engagement across nuclear security, disarmament dialogue, and global technical discussion.
United Nations Office for Disarmament Affairs (UNODA)
Selected as a Youth Leader Fellow for the Youth Leader Fund for a World Without Nuclear Weapons, contributing to international dialogue on nuclear security and related policy issues.
IAEA ICONS 2024, Vienna
Participated as a Youth Delegate in the Nuclear Security Delegation for the Future and contributed to international nuclear security discussions.
International Research and Policy Perspective
His profile combines technical research in nuclear and cyber systems with participation in international conversations on security, resilience, and the future of critical infrastructure.
Contact
For academic collaboration, research discussions, or professional inquiries, please get in touch via email or LinkedIn.
Primary Email
m.umut.ozbek@gmail.comAcademic Email
MustafaUmut.Ozbek@ontariotechu.caLocation
Oshawa, Ontario, Canada