Summary
Richard Bortsov is a machine learning scientist and engineer with 11 years of experience and a PhD (cum laude) in medical image analysis, now driving ethical, high-impact health data science as a postdoc at Leiden University. He specializes in deep learning for medical imaging—developing robust segmentation models, semi- and weakly-supervised methods, and adversarial-robustness guidelines—and has translated research into clinically relevant tools such as automated intracranial calcification quantification. Proficient in Python, TensorFlow/Keras, R, C/C++, SQL and Linux, he pairs strong engineering skills with close collaborations with epidemiologists and clinicians to ensure models are interpretable and useful in practice. He moves rapidly between topics and methodologies, having contributed across diverse ML domains from microscopy to population health, and maintains an active research footprint visible on Google Scholar. An understated strength is his track record in turning rigorous research into evaluation pipelines and deployment-minded validation (A/B testing) that bridge academia and clinical application.
11 years of coding experience
2 years of employment as a software developer
Master of Science (M.Sc.), Computer Science, highest distinction, top 3.5% of the class, GPA equivalent 3.9/4.0, Master of Science (M.Sc.), Computer Science, highest distinction, top 3.5% of the class, GPA equivalent 3.9/4.0 at Technical University Munich
Bachelor of Science - BS, Information Systems, graduated with honors, GPA 3.86/4.00, Bachelor of Science - BS, Information Systems, graduated with honors, GPA 3.86/4.00 at Kazakh-British Technical University
High School Certificate, High School Certificate at ГСШМФИ №25
Doctor of Philosophy - PhD, Medical Image Analysis, cum laude, Doctor of Philosophy - PhD, Medical Image Analysis, cum laude at Erasmus University Rotterdam
English, Russian, German, Kazakh, Dutch