Sebastian Dalleiger

Sebastian Dalleiger is a Tenure Track Assistant Professor in Machine Learning at KTH Royal Institute of Technology's Theoretical Computer Science division in Stockholm, Sweden. His research bridges foundational machine learning, responsible AI, and data analysis algorithms with applications in the natural sciences.

• Current affiliation: KTH Royal Institute of Technology (Theoretical Computer Science)
• Research focus: Theoretically grounded methods for machine learning, responsible AI, and data analysis
• Application areas: Natural sciences, multi-graph analysis, and privacy-preserving techniques

His recent work explores federated learning, matrix factorization, and pattern discovery across multiple datasets. Current research trends include geometric approaches to hypergraphs, entropy optimization, and explainable data decompositions.