Research Interests

Machine learning and statistical signal processing：
Classification, supervised learning
Kernel methods, Support Vector Machines
Optimization with sparsity, variable selection, mixed norms, non convex regularization
Feature learning, data representation, kernel learning
Convolutional neural networks, filter learning, image reconstruction
Optimal transport, domain adaptation

Applications：
Biomedical engineering, Brain-Computer Interfaces
Remote sensing and hyperspectral Imaging
Energy and climate
Astronomical image processing