Summary
Pablo Gómez is a data scientist and research engineer with 12 years of experience applying deep learning, numerical simulation and applied mathematics to medical imaging, genomics and remote sensing. He holds a Dr.-Ing. in Medical Image Processing and has built and deployed research-grade software—from high-speed endoscopic video analysis tools to onboard ML systems for the European Space Agency. At ESA he has led interdisciplinary studies on space debris, onboard disaster detection and modeling constraints for spacecraft, while earlier work translated genomic and clinical questions into ML products at Quantgene. Comfortable bridging academia and operational teams, he frequently supervises students, organizes scientific events, and drives open collaboration across institutions. A not-obvious strength is his blend of HPC-aware algorithm design and practical deployment experience, enabling models that scale from lab prototypes to onboard space hardware.
12 years of coding experience
4 years of employment as a software developer
Bachelor of Science (BSc), Computer Science, Bachelor of Science (BSc), Computer Science at Technische Universität München / TU Munich
Abitur, Mathematics, Physics, Abitur, Mathematics, Physics at Marie Therese Gymnasium, Erlangen
Master of Science (M.Sc.), Computer Science, Master of Science (M.Sc.), Computer Science at Technische Universität München
Doctor of Engineering (Dr.-Ing.), Medical Image Processing with Deep Learning, Doctor of Engineering (Dr.-Ing.), Medical Image Processing with Deep Learning at University of Erlangen-Nuremberg
German, English, Spanish, Swedish