Summary
Stefanos Panagiotou is a Machine Learning Researcher and PhD candidate at the University of Patras with nine years of experience applying Industrial AI and IIoT to real-world manufacturing problems like predictive maintenance, product quality monitoring, and structural health monitoring. He leads end-to-end applied research projects—finding funding, writing proposals, coordinating stakeholders, and deploying ML models in live production—demonstrated by a deployed system that helped prevent defects on a 60,000-bottles-per-hour beer line. His technical work spans time-series forecasting, 1D conv-transformer models, TinyML on edge devices, transfer learning with synthetic and experimental data, and practical MLOps for real-time inference. Comfortable across academia and industry, he also teaches statistics, supervises theses, and bridges mechanical engineering and IoT teams to translate sensor data into actionable KPIs. Notably, he complements deep technical skills with proposal and project management experience across EU and national research programs, enabling measurable impact beyond prototypes.
9 years of coding experience
1 year of employment as a software developer
Machine Learning Summer School (MLSS), Machine Learning Summer School (MLSS) at Okinawa Institute of Science and Technology
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Patras
Mediterranean Machine Learning Summer School (M2L), Mediterranean Machine Learning Summer School (M2L) at Università degli Studi di Milano-Bicocca
POLITEHNICA București National University for Science and Technology
English, Greek, Finnish, French