I am a Research Faculty member of the Mathematical Institute for Data Science (MINDS) of the Johns Hopkins University working with Prof. Rene Vidal. 

My research interests span the areas of machine learning and signal processing. More specifically, the overarching goal of my research endeavors is to devise efficient and reliable algorithms for analyzing high-dimensional and large-scale datasets. These datasets could be generated by medical imaging modalities, satellite cameras, remote sensing sensors, internet applications, etc. My work is interdisciplinary and touches upon topics at the intersection of convex/nonconvex optimization theory and approximate Bayesian inference, representation learning, high-dimensional probability theory, image processing, computer vision, etc.  My latest research interests are in the areas of adversarial learning, continual learning and inverse problems using deep generative models. A comprehensive list of my publications can be found here.

In 2011, I  received a Diploma degree in electrical and computer engineering from the National Technical University of Athens, Athens. In 2014 I obtained the M.Sc. degree in Information Technologies in Medicine and Biology and in July 2018 a Ph.D. degree from the University of Athens. During my Ph.D. I worked under the supervision of Dr. Athanasios Rontogiannis and Dr. Konstantinos Koutroumbas at the National Observatory of Athens. My Ph.D. thesis touched upon nonconvex optimization algorithms for structured matrix estimation with applications to remote sensing, audio signal processing, and recommender systems.