Bryon Aragam studies high-dimensional statistics, machine learning, and optimization. His research focuses on mathematical aspects of data science and statistical machine learning in nontraditional settings, such as heterogeneity and nonconvexity. Some of his recent projects include problems in graphical modeling, nonparametric statistics, personalization, and high-dimensional inference. He is also involved in open-source software development and problems in interpretability, ethics, and fairness in AI. His work has been published in top statistics and machine learning venues...