His research is making fundamental advances in machine learning, network and data science, especially in the areas of link prediction, higher order networks, co-evolution and dynamics of networks, learning from imbalanced data, distributed learning, concept drift, and evaluation issues for machine learning and data mining algorithms. His research is bridging disciplinary boundaries for transformative applications in healthcare, education, environment, and national security --- technology meets society to augment human intelligence and creativity.