Research Areas Theory and applications of convex and non-convex optimization in large-scale machine learning and data science problems

Nicolas Loizou is an assistant professor in the Department of Applied Mathematics and Statistics, with a secondary appointment in the Department of Computer Science and affiliation with the Mathematical Institute for Data Science.

His research interests include large-scale optimization, machine learning, randomized algorithms, randomized numerical linear algebra, distributed and decentralized algorithms, and game theory. His current research focuses on the theory and applications of convex and non-convex optimization in large-scale machine learning and data science problems. He has received several awards and fellowships, including OR Society’s 2019 Doctoral Award (runner up) for the ”Most Distinguished Body of Research leading to the Award of a Doctorate in the field of Operational Research,” the IVADO postdoctoral fellowship, and COAP 2020 “Best Paper” award.

Before joining Johns Hopkins in January 2022, he was an IVADO postdoctoral fellow at Mila-Quebec Artificial Intelligence Institute and DIRO at the Université de Montréal. He received his doctoral in operational research and optimization at the University of Edinburgh, School of Mathematics, in 2019; his master’s degree in computing at Imperial College London in 2015; and his bachelor’s in mathematics at National and Kapodistrian University of Athens in 2014.