Rate My Professor Vasileios Maroulas

Maroulas specializes in artificial intelligence, machine learning, computational probability, statistics, and topological and geometric data analysis, addressing challenges in biology, medicine, materials science, and national defense. His publications have exceeded 2,000 citations, including "Large deviations for infinite dimensional stochastic dynamical systems" (Annals of Probability, 2008), "Representation of molecular structures with persistent homology for machine learning applications in chemistry" (Nature Communications, 2020), "Variational representations for continuous time processes" (Annales de l'Institut Henri Poincaré Probabilités et statistiques, 2011), "Polymer graph neural networks for multitask property learning" (npj Computational Materials, 2023), and "A Bayesian framework for persistent homology" (SIAM Journal on Mathematics of Data Science, 2020). Notable awards include the Early-Career Faculty Research and Creative Achievement Award from the College of Arts & Sciences, University of Tennessee (2014), Leverhulme Trust Fellowship (2012), and Eleneio Doctoral Thesis Award from the Greek Statistical Society (2009). He serves as Chief Editor of Foundations of Data Science, Editor of Statistics and Computing, and Senior Advisory Editor of ACM Transactions on Probabilistic Machine Learning. The Maroulas Research Group has obtained funding from AFOSR, ARO, DOE, NSF, VA, national laboratories, and private foundations.