Summary
Aydin Abedinia is a machine learning researcher and distributed systems engineer with 11 years of experience, who has transitioned from building production-scale AI at Snapp—where he led MLOps and migrated systems from monolith to resilient microservices—to pursuing a Joint European PhD across Genova, Madrid, and London focused on cognition and human-centered AI. He combines hands-on expertise in Python, Go, and Rust with practical MLOps know-how, having shipped ML features used by millions and built infrastructure that endured heavy demand. His publications on semi-supervised learning, distance-based sample weighting, and decision tree optimization reflect a research-driven curiosity about why models work as much as how to deploy them. Comfortable at the nexus of theory and impact, he seeks to bridge rigorous research with production realities and collaborate with teams tackling meaningful AI problems across Europe and beyond.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy, Artificial Intelligence, Doctor of Philosophy, Artificial Intelligence at Università degli Studi di Genova
Doctor of Philosophy, Artificial Intelligence / Cognitive Environment, Doctor of Philosophy, Artificial Intelligence / Cognitive Environment at Queen Mary University of London
Charles III University of Madrid (Universidad Carlos III de Madrid)
Master of Science - MS, Computer Software Engineering, Master of Science - MS, Computer Software Engineering at Azad University (IAU)
Diploma, Mathematics and Physics, Diploma, Mathematics and Physics at Mollasadra Highschool
English, Turkish, Persian