معرفی
Simon Süwer is a Research Associate and PhD student at the Computational Systems Biology (CoSy.Bio) department within the Faculty of Mathematics, Informatics and Natural Sciences at the University of Hamburg. His work focuses on developing privacy-preserving tools for federated collaboration, aiming to bridge theoretical and practical challenges in data-sharing frameworks. He is involved in the FeatureCloud (https://featurecloud.ai/) and dAIbetes projects, which emphasize innovative solutions for secure, effortless data collaboration.
Education: Simon holds a Bachelor of Science in Applied Computer Science from the University of Applied Sciences and Arts Hannover and a Master of Science in Computer Science from the University of Vienna, specializing in Data Science. His master’s thesis explored hierarchical dynamic Graph Neural Networks (GNNs) for session- and sequence-based recommender systems.
Research Interests: His current research emphasizes federated learning, privacy-preserving methodologies, and the integration of dynamic graph models. He seeks to redefine data collaboration paradigms through interdisciplinary approaches, merging computational techniques with real-world applicability.
Labs/Teams: Active contributor to CoSy.Bio and the FeatureCloud initiative, advancing decentralized AI frameworks for healthcare and beyond.
