Sibylle Hess has successfully defended her dissertation A Mathematical Theory of Making Hard Decisions: Model Selection and Robustness of Matrix Factorization with Binary Constraints at the Chair of Artificial Intelligence. She developed new methodologies for two branches of clustering: the one concerns the derivation of nonconvex clusters, known as spectral clustering; the other addresses the identification of biclusters, a set of samples together with similarity defining features, via Boolean matrix factorization. 

The members of the doctoral committee were Prof. Dr. Katharina Morik (supervisor and first examiner), Prof. Dr. Arno Siebes (second examiner, University of Utrecht) and Prof. Dr. Erich Schubert (representative of the faculty). Sibylle Hess was a research assistant at LS8, a member of the Collaborative Research Center 876 (Project C1) and now works as a postdoctoral fellow at the TU Eindhoven.