I am doing research on the intersections between machine learning, information theory and signal processing, which include topics like information-theoretic learning and machine learning for signal processing. Particularly, I am interested in information-theoretic quantities (such as entropy, mutual information, divergence, etc.) estimation, improving the explainability and generalization of deep neural networks by information-theoretic principles (such as the information bottleneck and the principle of relevant information). I am also interested in brain data analysis (such as EEG and fMRI).