Research experience spans geometric deep learning, learning embeddings and representations, dynamics and optimal transport, multiscale graph signal processing, and applications in biomedical systems.
Background
Research interests include the development of foundational mathematical machine learning and deep learning methods that incorporate signal processing, data geometry, and topology to enable exploratory analysis, scientific inference, and prediction from big biomedical datasets.
Miscellany
The lab is located across the beautiful Yale campus in New Haven, Connecticut.