AI · Airworthiness · Aviation
Making AI airworthy.
I'm Göksu Anıl Kızıldoğan — a principal data scientist with over ten years of building machine learning in industry, and a PhD researcher in aviation technologies. I work where large language models meet airworthiness: AI that engineers, operators and regulators can actually trust.
- 10+ yrsData science & machine learning in industry
- PhDAviation Technologies, Eskişehir Osmangazi University
- LLM · RAGEnterprise AI systems, on-premise and in the cloud
- AI & MLEnd to end ML/AI solutions for various industries
The name
A play on words — and a research agenda.
air·wor·thi·ness
noun
The fitness of an aircraft for safe flight — shown through conformity to an approved design, evidence and continued oversight.
AI·wor·thi·ness
noun
The same discipline, applied to artificial intelligence: models whose data, behaviour and limits are traceable, verifiable and certifiable before they are trusted in aviation.
Focus areas
What I work on
LLMs for certification documents
RAG and fine-tuning pipelines that let engineers query regulations such as EASA CS-E — with answers grounded in, and traceable to, the source text.
Flight safety & risk prediction
Machine learning on civil aviation data to anticipate risk before it turns into an occurrence.
AI in avionics
How AI reshapes flight control, sensor fusion, predictive maintenance, air traffic management and avionics software certification.
Production ML & MLOps
A decade of shipping models: IoT analytics, forecasting, anomaly detection, on-premise LLMs and the pipelines that keep them healthy.
Let's talk about trustworthy AI in aviation.
Research collaborations, industry projects, or just an interesting question — I'm happy to hear from you.