Machine Learning & Mission-Critical Systems
U.S. Ph.D. (Embry-Riddle, 2025) in machine learning security. Four first-author papers, three in IEEE Access. Twelve years on mission-critical systems.
Page Archive
Field Notes
Field notes on ML security, proof-of-learning, distributed systems, and high-reliability software for researchers, engineers, and technical leaders.
Posts by Category
Posts organised by category: machine learning, security, engineering, and more.
Posts by Collection
Browse all publications, talks, and portfolio items on ozgurural.github.io.
Essays
Slow, indirect writing about machine learning, security, and the systems we are quietly building.
What a blockchain buys machine learning
Strangers want to train one AI model together. A narrated film on what a blockchain adds: a record nobody can quietly rewrite, work aimed at training, pay by contribution, and what the prototypes measured (Ural & Yoshigoe, IEEE Access 2023).
Hearing an attack in the noise
A website goes down, and people post about it before any statement. A narrated film on detecting cyber security events from Turkish posts and news without a labelled data set (Ural & Acarturk, ICISSP 2021).
AI meets the deadline
An AI can plan a robot’s next move. What if the answer arrives after it was needed? A narrated film on keeping an AI planner out of a real-time controller’s waiting path. An open research direction of the author, not yet published.
A walk downhill
How does a machine actually learn? A narrated film on gradient descent: the step, why its size matters, momentum in narrow valleys, and saddle points.
Inside a Level D flight simulator
A narrated film by Dr. Ozgur Ural: how a Level D full-flight simulator fools a pilot’s senses, how it is proven against the real aircraft, why it can never be late, and what that means for AI in the loop.
A whisper in the weights
Your AI model leaks and someone retrains it a little. A narrated film on how a faint mark spread across many weights can still be read back out of the noise, and where that test stops.
A backup that shares your mistake
Three computers agree. Could all three still be wrong? A narrated film on majority voting, common-cause failure and the loss of Ariane 5, whose two identical navigation computers failed the same way.
SecurePoL, animated
Someone copies your AI model. How do you prove it was yours? A two-minute narrated film on SecurePoL (Ural & Yoshigoe, IEEE Access 2025): keep the trail that training leaves, and plant a secret in the model that only its owner can ask for.
Signing an AI model
Your AI model has been stolen and runs inside someone else’s product. How do you show it is yours? A narrated film on model watermarking: three places to hide a signature in a model, and why it should be tied to the training record (Ural & Yoshigoe, IEEE Access 2025).
Blockchain-Enhanced Machine Learning, animated
What a ledger buys machine learning: consensus that trains instead of hashing, contracts that pay for the improvement you caused, and the measured limits.
Detecting Cyber-Security Events in a Low-Resource Language, animated
Detecting cyber-security events with no labelled corpus: a keyword vector learned from the nic.tr attack, Turkish morphology, and anomalies per entity.
AI Meets the Deadline
Explore how AI planning meets real-time execution: an animated architecture experiment with latency, stale proposals, fallback and resource contention.
Gradient Pinball: how machines learn, animated
A cinematic, PhD-level explainer on gradient descent, momentum, and why high-dimensional loss landscapes are ruled by saddle points, not local minima.
Universal Jira: Prediction Markets for Global Coordination, animated
A cinematic explainer on how smart contracts and prediction markets can act as incentive-compatible coordination with no trusted central party.
Inside a Level D Flight Simulator
How a Level D flight simulator fools a pilot’s senses, is proven against the real aircraft and is never late, and what that means for AI in the loop.
ML Oracles: Verifiable Claims for the Chain, animated
Can a contract trust an AI answer it did not compute? An animated comparison of zero-knowledge proofs, optimistic challenges, and their limits.
Proof-of-Learning (SecurePoL), animated
How Proof-of-Learning checks training records, where spoofing attacks exploit it, and how SecurePoL combines trajectory and watermark verification.
Block Race: Nakamoto consensus, animated
Why ‘6 confirmations’ is a probability, not a promise. A cinematic, PhD-level walk through the double-spend math of Bitcoin’s whitepaper §11.
Redundancy Reactor: fault tolerance, animated
Majority voting buys superlinear safety, until correlation installs a floor you cannot vote past. An animated explainer ending in the Ariane 5 loss.
Signing an AI model: model watermarking, animated
A narrated film on model watermarking: three places to hide a signature in a model (its answers, its weights, an auxiliary head), and why the mark should be tied to the training record.
Model Heist Detector: AI watermarks, animated
How a watermark too faint to see in any single weight can become detectable across thousands of them under an explicit statistical model. A cinematic Z-test explainer.
Research Lab
Block Race, Model Heist Detector, SecurePoL, Redundancy Reactor, Gradient Pinball, ML Oracles and more. Real research math, animated from the equation up.
Perspectives & Leadership
Essays on system architecture, engineering leadership, and what twelve years of shipping mission-critical software teaches about resilient systems.
Projects
AI and ML projects by Dr. Ozgur Ural spanning model provenance, verifiable inference, autonomous agents, safety-critical systems, and human-verified clinical tools.
Publications
Peer-reviewed publications by Dr. Ozgur Ural on proof-of-learning, model watermarking, adversarial robustness, and blockchain-enhanced machine learning.
Advisory & Service
Technical advisory, ML security and model provenance review, conference speaking, peer review, and program-committee service.
Sitemap
A full list of all posts, pages, and publications on ozgurural.github.io.
Privacy and Site Use
How this portfolio handles hosting, external services, and contact messages.