Summary
Stephan Lorenzen is a Lead Data Scientist with 11 years of experience blending rigorous academic research (PhD and postdoc from the University of Copenhagen) with hands-on ML and algorithm engineering in digital education and health. He currently leads health-AI efforts at Aiomic, focusing on detection and prediction of postoperative complications using efficient, practical approaches that range from theoretically grounded algorithms to parallelized implementations. Comfortable in C/C++ for performance-critical systems and Python for analysis, he repeatedly bridges the gap between prototype research and production-ready solutions. His background in big data, deep learning theory, and Danish health data gives him a strong domain edge in clinical applications. Outside work he prioritizes a healthy, active lifestyle—often hiking, running or kayaking—which he credits for sustaining long-term problem-solving stamina.
11 years of coding experience
5 years of employment as a software developer
Master of Science (MSc), Computer Science, Master of Science (MSc), Computer Science at Københavns Universitet
STX, Mathematics, Physics and Chemistry, STX, Mathematics, Physics and Chemistry at Rosborg Gymnasium
Danish, English, German