We are working on core models and algorithms in machine learning. One long-term interest is in deep network architectures. We are interested both in new layers and operators, and in new macroscopic structures and connectivity patterns. Another interest is the development of deep learning techniques for discrete structures, such as graphs and sets, and combinatorial optimization problems. Another line of work concerns settings such as continual learning, which depart from conventional offline batch supervised learning.