Vlad received his Ph.D. in Applied Mathematics from Washington State University in December 2019. His research interests include network science, geometric data analysis, and machine learning. Vlad’s current research aims to use Bayesian inference for causality analysis of operational data from OLCF HPC systems, and to step up the scale of distributed deep learning by leveraging knowledge distillation networks.