My research is mainly focused on the intersection between machine learning and signal processing. I am interested in theory and practice of the following challenges: • Unsupervised learning- extracting latent parameters from high dimensional or multi-modal data. • Interpretability- exploiting sparsity to learn robust interpretable models that lead to the identification of predictive variables. • Generative Models- synthesizing reliable artificial data to enhance the prevalence of rare sub-population in biological/dynamical processes.