Advisory & Service
I advise engineering teams and technical leadership on verifiable, trustworthy ML, model provenance, and high-reliability architecture, the trust infrastructure that lets AI ship into systems where failure is not an option. I also serve the research community as a reviewer and program-committee member. Full publication record on Google Scholar. For engagements: drozgurural@gmail.com.
Advisory & speaking
Trustworthy-ML & model-provenance review
Independent assessment of training-integrity, watermarking, and model-provenance claims, grounded in my published proof-of-learning research. For teams shipping, buying, or auditing ML systems.
Mission-critical architecture review
Design reviews for real-time and fault-tolerant systems, drawing on twelve years across defence, cybersecurity, and Level D flight simulation, including engineering leadership across complex products.
Talks & guest lectures
Conference talks and guest lectures on proof-of-learning, model watermarking, and engineering systems that stay correct when things fail. See the Research Lab for a preview of how I teach these ideas.
Research service
NLPAICS 2026, University of Alicante
2nd Workshop on NLP Applied to Information and Cyber Security. Reviewing submissions on NLP for threat intelligence, abuse detection, and defensive cyber.
IEEE Access and peer-reviewed journals in ML security & distributed systems
Manuscript review across ML security, privacy, distributed systems, and intelligent infrastructure. Frequent reviewer for IEEE Access in the secure-ML track.
IEEE conferences & symposia
Computer security, data privacy, machine learning, distributed systems, blockchain.
For service invitations, collaborations, or talks: drozgurural@gmail.com.