Aasa Feragen

December 08, 2016

The research of Aasa Feragen is on geometric methods for machine learning and statistics, often applied in medical image analysis. She develops mathematical models and algorithms for data with complex structure, where the complexity usually comes from geometric constraints, combinatorial properties such as branching structure, or both. Her talk will be on uncertainty quantification in tractography for diffusion MRI, and she hopes to gain feedback from practitioners on the potential utility of the model in the clinic, and potentially even future collaborations taking the research prototypes to a more practically useful stage.