Dr. Ozgur Ural
Dr. Ozgur Ural

Ph.D. in Machine Learning | Trustworthy-ML researcher | Architect of mission-critical systems

Verifiable & Trustworthy ML · Applied GenAI · Mission-Critical Systems

I design verifiable ML and mission-critical systems, establishing the standards that keep them correct when things fail.

I'm Dr. Ozgur Ural, a senior software engineer and machine-learning researcher. Across Turkey, the United States, and the Netherlands, I've spent twelve years architecting systems that cannot be allowed to fail: real-time ground-control software for pioneering autonomous UAV programs, a national-scale data-leakage-prevention platform, and the real-time Level D flight-simulator platforms I build today at Avion. My Ph.D. in Machine Learning (ERAU, 2025) and my published research on proof-of-learning, model watermarking, and adversarial robustness give that engineering a research spine: I publish the methods that prove ML systems can be trusted, then apply them in production. As AI moves into decisions that cannot be allowed to fail, the scarce resource is no longer intelligence — it is trust you can prove. Building that trust infrastructure is the through-line of my work.

Amsterdam, Netherlands. Building flight-simulation platforms and publishing ML-security research. Open to advisory, speaking, and research collaboration.

Read my research Advisory & speaking Get in touch
  • 12+Years in mission-critical software
  • Ph.D.Machine Learning · ERAU 2025
  • 5First-author papers · 3 in IEEE Access
  • IEEEJournal referee · NLPAICS'26 program committee

Leadership & Core Domains

My work sits at the intersection of deep technical expertise and organizational scale: setting architectural direction, raising engineering standards, and ensuring that complex systems, from mission-critical C++ to cloud-native microservices, remain robust under extreme conditions.

  • Engineering Leadership

    Direction, standards, teams

    Having shipped national data-leakage-prevention products and mission-critical software, today I drive architecture decisions and technical standards that raise the bar across the engineering organization: resilience patterns, review culture, and release discipline.

  • Fault-Tolerant Distributed Systems

    Fault-tolerant by design

    Real-time simulation platforms and cloud-native services (C++, Scala, TypeScript, gRPC) built on distributed protocols whose outputs and state can be audited end-to-end without compromising latency.

  • Trustworthy ML & Security

    Securing AI pipelines

    Deep domain expertise in defending ML training integrity against spoofing attacks. My Ph.D. and IEEE-published research focus on feature-based model watermarking and proof-of-learning verification.

  • Adversarial Robustness

    Models that survive adversaries

    Bridging research and production by ensuring models survive contact with adversaries. Evaluating provenance verification, adversarial examples, and the limits of claimed model identities.

Timeline

  1. 2026 Leading Avion's enterprise AI strategy: authored the AI adoption roadmap and a three-tier architecture (air-gapped on-prem LLMs, a governed cloud-LLM API tier, and edge), then designed and shipped a suite of retrieval-augmented and autonomous agents, including an engineering-knowledge copilot with grounded citations, an autonomous repository agent, an RFP accelerator, and a training-debrief writer.
  2. Dec 2025 Published SecurePoL: Integration of Watermarking with Proof-of-Learning to Enhance Security Against Spoofing Attacks in IEEE Access. Read paper.
  3. Dec 2025 Joined the Program Committee for the 2nd Workshop on NLP Applied to Information and Cyber Security (NLPAICS 2026), University of Alicante. Conference.
  4. Aug 2025 Conferred Ph.D. in Electrical Engineering & Computer Science (ERAU). Dissertation: Enhancing Proof-of-Learning Security Against Spoofing Attacks Using Model Watermarking. My doctoral research was guided by Dr. Kenji Yoshigoe (Committee Chair) and IEEE Fellow Dr. Houbing Song, with whom I continue to actively collaborate on securing distributed ML systems. Dissertation · Verify diploma.
  5. 2021–2025 Graduate Research Assistant at Embry-Riddle Aeronautical University. Three IEEE Access publications on proof-of-learning and model watermarking.
  6. Nov 2024 First-author paper Feature-Based Model Watermarking for PoL in IEEE Access. Read paper.
  7. Dec 2023 Published the survey Blockchain-Enhanced Machine Learning in IEEE Access. Read paper.
  8. Oct 2023 Joined Avion Full Flight Simulators as Senior Software Engineer. Architecting real-time simulation platforms and cloud-native infrastructure for Level D flight simulators.
  9. May 2021 Published Automatic Detection of Cyber Security Events from Turkish Twitter Stream and Newspaper Data at ICISSP. Read paper.
  10. 2020–2021 Software Team Lead at Havelsan. Led a 14-engineer team delivering the Havelsan DLP data leakage prevention product for defence and government clients.
  11. 2019–2020 Expert Software Engineer at STM Defence Technologies. Architected mission-control and ground-control software for the Kargu and Togan programs, among Turkey's first indigenous autonomous UAV systems, where real-time reliability was safety-critical.
  12. 2014–2019 Expert Software Engineer at Comodo Cybersecurity. Led design and architecture of the Secure Web Gateway, enterprise Patch Manager, and the Chromium-based Dragon browser.

Selected Work

Scientific Impact & Professional Service

My methodologies in decentralized trust and model watermarking have been adopted by peers to protect AI ownership and lineage, appearing in premier venues such as IEEE Transactions on Services Computing and IEEE SaTML 2026. This work provides efficient mechanisms for securing critical infrastructure against adversarial AI threats, directly supporting the national security priorities outlined in the Executive Order on Promoting the Export of the American AI Technology Stack.

Recognized for my expertise in secure and distributed machine learning, I actively serve the scientific community by evaluating cutting-edge research:

  • Journal Referee, IEEE Access, and other peer-reviewed journals in ML security, privacy, and distributed systems
  • Program Committee Member, 2nd Workshop on NLP Applied to Information and Cyber Security (NLPAICS 2026), University of Alicante
  • Reviewer, IEEE and ACM conferences in security, machine learning, and distributed systems

Get in touch

For research collaboration, technical advisory, or speaking engagements, reach out by email, or browse my publications, projects, and technical writing.