Bastian Rieck
Principal Investigator“Changing our perspective helps us see the world in a whole new light. Solving the upcoming challenges in the life sciences thus requires machine learning algorithms that are aware of multiple scales in the data.”
“Changing our perspective helps us see the world in a whole new light. Solving the upcoming challenges in the life sciences thus requires machine learning algorithms that are aware of multiple scales in the data.”
Research Areas
Our world is full of phenomena that occur at multiple scales. Biomedical research, for instance, commonly observes complex systems at different resolutions, ranging from the macroscopic to the microscopic. With noise being an inevitable part of such investigations, we need tools that enable robust multi-scale analyses. My research agenda is to create, cultivate, and critique such tools based on topological machine learning techniques, with a specific focus on healthcare topics.
About
Bastian A. Rieck (M.Sc., Ph.D.) is the Principal Investigator of the AIDOS Lab at the Institute of AI for Health and the Helmholtz Pioneer Campus of Helmholtz Munich, focusing on topology-driven machine learning methods in biomedicine. Dr. Rieck is a member of European Laboratory for Learning and Intelligent Systems, and also serves as the co-Director of the Applied Algebraic Topology Research Network (AATRN).
Skills
Topological Machine LearningDeep LearningGeometrical Deep LearningGraph LearningGraph Neural NetworksBioinformatics
Time periods & Career steps
Ph.D. (summa cum laude): “Persistent Homology in Multivariate Data Visualization”
Postdoctoral Researcher at ETH Zurich, Machine Learning and Computational Biology Laboratory (MLCB)
Senior Assistant at ETH Zurich, Machine Learning and Computational Biology Laboratory (MLCB)
Research Group at Helmholtz Munich, Institute of AI for Health
Networks and Affiliations
