Bastian Rieck

Bastian Rieck is a Full Professor of Machine Learning at the University of Fribourg and a Principal Investigator at the Institute of AI for Health and Helmholtz Pioneer Campus of Helmholtz Munich. He leads the AIDOS Lab, focusing on topology-driven machine learning methods in biomedicine, and serves as co-Director of the Applied Algebraic Topology Research Network (AATRN).

Research Interests: His work bridges topological machine learning, geometrical deep learning, and graph neural networks to address challenges in biomedicine. He advocates for integrating point set topology, algebraic topology, and differential topology into machine learning models for robust, explainable science.

Scientific Awards:

• ERC Starting Grant for the HOLES project
• TUM Junior Fellow
• Member of ELLIS

Collaborations & Funding: Supported by the Canton of Fribourg, Hightech Agenda Bavaria, and Swiss SERI, he collaborates with institutions like ETH Zurich and maintains initiatives such as DONUT (Database of Original & Non-Theoretical Uses of Topology).