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arising in healthcare and environmental applications.
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Our primary research interests are situated at the intersection of
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**geometry, topology, and machine learning**. From data-centric evaluation frameworks to novel architecture developments, we make use of geometrical and
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topological information to imbue our methods with foundations that foster interpretability and robustness. Along the way, we develop new **manifold learning** techniques, new
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**representation learning** algorithms, and much more.
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