Misha Salim leads development of the Balsam workflow system at ALCF and is a core developer of the DeepHyper framework for tuning deep learning models at scale. He received a Ph.D. in physical chemistry from the University of Illinois at Urbana-Champaign, where he worked with So Hirata on first-principles simulations of liquid water and ice. As a postdoctoral appointee, he works with Balsam users to build data-intensive workflows in projects spanning high energy physics, chemistry and materials science, global optimization, machine learning, and experimental data analysis. Misha’s engineering efforts on the Balsam project are centered on distributed-system workflows and exposing HPC resources to experimental data producers. His research interests lie at the intersection of computational chemistry and machine learning, particularly where surrogate models can be trained to accelerate costly ab initio simulations.