Nicholas André G. Johnson

Nicholas André G. Johnson has engaged in optimization and machine learning research at The Massachusetts Institute of Technology (MIT), Princeton University, Oxford University and the Montreal Institute of Learning Algorithms. He is currently a PhD student in Operations Research, the study of how to make good decisions with limited information in uncertain environments, at MIT where he is working towards developing a more unified theory of optimization and machine learning. Nicholas holds an undergraduate degree with highest honours in operations research and financial engineering with minors in computer science, statistics and machine learning, and applied and computational mathematics from Princeton University. He was the Valedictorian of Princeton’s Class of 2020 and is the first Black Valedictorian in the University’s 274 year history.

His undergraduate thesis focused on developing high performance, efficient algorithms to solve a network based optimization problem that models a community based preventative health intervention designed to curb the prevalence of obesity in Canada. Nicholas has interned as a software engineer at Google and as a quantitative developer at the D. E. Shaw Investment Group, and has conducted and presented international sustainable engineering projects at the United Nations Headquarters. He is a member of the Phi Beta Kappa, Tau Beta Pi and Sigma Xi honor societies. Nicholas has previously been featured by the New York Times, CNN, ABC News, Time and BET.