Maria Maros earned a PhD in Information Science and Engineering from the KTH Royal Institute of Technology, Stockholm, Sweden. She worked with co-advisors, Dr. Gesualdo Scutari, Professor of Industrial Engineering, and Dr. Guang Cheng, Professor of Statistics, to develop a theory of the fundamental tradeoffs that govern statistical learning in a large-scale nonconvex networked setting. Her research interests include distributed optimization methods in time varying environments. She continues her postdoctoral research work with Dr. Scutari and in January 2022 the team published a study on sparse linear regression over a network of agents, modeled as an undirected graph and no server node.