Dr. Bryon Aragam

Biography

Bryon Aragam studies causality, statistical machine learning, and probabilistic modeling. His current research interests encompass causal machine learning, deep generative models, latent variable models, and statistical learning theory. He particularly focuses on applications of artificial intelligence, including tools like ChatGPT and DALL-E. He has been involved in developing open-source software to address issues related to interpretability, ethics, and fairness in artificial intelligence. His work has been published in leading statistics and machine learning venues such as the Annals of Statistics, Neural Information Processing Systems, International Conference on Machine Learning, and the Journal of Machine Learning Research. Before joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Bryon completed his PhD in Statistics and a Master's in Applied Mathematics at UCLA, where he was also an NSF graduate research fellow. Additionally, he has served as a data science consultant for technology marketing firms, working on survey design methodology, ranking, customer retention, and logistics.

Research Interests

Courses