Academic Profile
Dr. Leo Sylvio Rüdian is a computer scientist whose work connects machine learning, responsible AI, predictive analytics, software engineering, and technology-enhanced learning. His research focuses on how data-driven and generative AI methods can be designed, evaluated, and transferred into robust systems that remain transparent, controllable, and useful in practice.
He studied computer science at Humboldt-Universität zu Berlin with a focus on machine learning and natural language processing. His Master’s thesis examined fingerprinting and de-anonymization in social networks; his doctoral research investigated personalization in online courses, generated course material, and adaptive sequencing strategies.
Responsible Systems
Human-centered and auditable AI processes from design to deployment.
Predictive Analytics
Quantitative methods, model evaluation, data-driven decision support, and interpretable workflows.
Learning Technologies
Learning analytics, educational data mining, adaptive learning, and formative feedback systems.
Research Focus
Research and Transfer
His work emphasizes the full analytical and technical process: data acquisition, preprocessing, modelling, validation, visualization, deployment, governance, and human-centered evaluation. A central question is how AI and analytics can become practically usable without becoming opaque black boxes.
Explore researchTeaching and Supervision
His teaching combines academic rigor with practical experimentation. Courses and supervision address data science, AI in education, prompt engineering, prompt evaluation, online-course design, and responsible use of AI methods.
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