Andrei Goncharov

I am a Machine Learning Engineer with over 5 years of experience specializing in medical imaging, deep learning, and product deployment. My work has had a proven impact, delivering TÜV-certified AI tools that are utilized in over 100 radiology clinics. I excel in building end-to-end machine learning pipelines and have a strong background in cloud infrastructure and real-world healthcare data.

At Floy GmbH, I built scalable ML pipelines for MRI and CT data, overseeing the entire process from acquisition and annotation to deployment. My contributions included designing and validating models for pathology detection, which led to the development of five TÜV-certified diagnostic tools. Additionally, I have engaged in research on large-scale self-supervised learning for 3D MRI segmentation, evaluating models across 13 clinical datasets.

Previously, I worked as an AI Engineer at Design AI GmbH, where I developed deep reinforcement learning agents for real-time strategy games and built a dense video captioning model. My academic background includes a Master’s degree in Robotics, Cognition, and Intelligence from the Technical University of Munich, where I focused on cardiac MRI segmentation using advanced self-supervised models.