Dr. Ozgur Ural

Ph.D. · ML Security · Distributed Systems · Aerospace

Building secure, distributed machine learning for systems that cannot fail.

I'm Dr. Ozgur Ural — a senior engineer and researcher operating at the intersection of artificial intelligence, distributed systems, and cybersecurity. My work spans peer-reviewed research on proof-of-learning and model watermarking, real-time C++ kernels powering FAA Level-D flight simulators, and cloud-native services in production. I help teams move trustworthy AI from paper to runtime.

Currently in Leiden, Netherlands  ·  open to research collaboration and technical advisory.

  • 11+Years engineering
  • Ph.D.ERAU · 2025
  • 4IEEE Access papers
  • PCNLPAICS 2026

Focus areas

  • AI / ML Security

    Trustworthy machine learning

    Proof-of-Learning protocols, feature-based model watermarking, adversarial robustness, blockchain-enhanced ML — published in IEEE Access.

  • Distributed Systems

    Production-grade architecture

    Cloud-native services in Scala, TypeScript, and gRPC. Designing for scale, resilience, and verifiability across heterogeneous workloads.

  • High-Reliability

    Aerospace simulation

    Real-time C++ kernels behind FAA Level-D Full Flight Simulators at Avion FFS — software where downtime is unacceptable.

  • Leadership

    Cross-functional direction

    A decade leading engineers, mentoring researchers, translating principled research into production-ready systems.

Recent

  1. Dec 2025 Joined the Program Committee for the 2nd Workshop on NLP Applied to Information and Cyber Security (NLPAICS 2026), University of Alicante. Conference.
  2. Dec 2025 Published SecurePoL: Integration of Watermarking with Proof-of-Learning to Enhance Security Against Spoofing Attacks in IEEE Access. Read paper.
  3. Aug 2025 Conferred Ph.D. in Electrical Engineering & Computer Science (ERAU). Dissertation: Enhancing Proof-of-Learning Security Against Spoofing Attacks Using Model Watermarking. Dissertation.
  4. Nov 2024 First-author paper Feature-Based Model Watermarking for PoL in IEEE Access. Read paper.
  5. Dec 2023 Published the survey Blockchain-Enhanced Machine Learning in IEEE Access. Read paper.

Get in touch

For research collaboration, technical advisory, or speaking engagements, please reach me at drozgurural@gmail.com.