Summary
Ronald Fecso is a PhD student and machine learning researcher with nine years of applied data science experience, currently advancing vision-language modeling for OCT retinal imaging at the Medical University of Vienna. He holds an MS in Machine Learning and Data Mining and spent an Erasmus semester at TU Wien, combining European research training with practical industry experience. His work spans end-to-end ML pipelines—from raw sensor data collection (radar and accelerometer) through PyTorch model training and real-time inference to deployment-ready systems for fall detection and road-quality assessment. Past roles at US federal agencies and healthcare organizations underscore strong quantitative research skills, reproducible data pipelines, and policy-minded visualization tools. He brings a rare blend of medical imaging research and embedded-sensor computer vision expertise, demonstrated by projects that moved from hardware signal processing to CNN/LSTM and 3D-CNN modeling.
9 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Machine Learning and Data Mining, Master of Science - MS, Machine Learning and Data Mining at Université Jean Monnet Saint-Etienne
Vienna University of Technology
Bachelor of Science - BS, Computational Modeling and Data Analytics (Math Minor), Cum Laude, Bachelor of Science - BS, Computational Modeling and Data Analytics (Math Minor), Cum Laude at Virginia Tech
Medical University of Vienna
English, French