Summary
Phillip Swazinna is a research-focused machine learning engineer with nine years of experience building and deploying advanced AI systems across medical imaging, reinforcement learning, and industrial applications. Trained at top European institutions and shaped by an exchange at UPenn, he turned early curiosity into a MSc and PhD trajectory—developing CNNs for neurodegenerative disease detection and model-based offline multi-task RL. At Siemens he translated state-of-the-art transformers, diffusion models and scalable training pipelines into real-world products, contributed open-source RL tools, and led funding and student mentorship; he now continues this applied-research path as a Research Scientist II at Microsoft. Known for blending rigorous statistical thinking (his bachelor’s work used epidemiological models to study scientific attention) with practical MLOps and cloud-scaled training, he excels at turning novel research into production-ready solutions.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, 1,7, Bachelor of Science - BS, Computer Science, 1,7 at Technische Universität Dortmund
ENGINEERING, 1,4, ENGINEERING, 1,4 at Télécom ParisTech
PhD Student, Multi Task Reinforcement Learning, PhD Student, Multi Task Reinforcement Learning at Technische Universität München
Computer and Information Sciences, General, 1,0, Computer and Information Sciences, General, 1,0 at University of Pennsylvania