Statistical modeling and learning use statistical models and assumptions to translate complex real-world problems into tractable structures so that predictions about uncertain outcomes or prescriptions to design systems can be made. Going from data to models, our methodological research in this area is shaped around devising novel frameworks that can lead to fair and interpretable decisions and insights. Key drivers to our fundamental research in this area are the explosion in the availability of data and computational powers in the last decade
