Ayana Ghosh

Dr. Ghosh’s research focuses on developing physics-based machine learning methods to investigate causal mechanisms in a wide range of materials ranging from inorganic perovskites, actinides, two-dimensional systems to organic counterparts. Bridging the gap between appropriately utilizing data generated by simulations and experiments require a great deal of understanding the nuances present in both fields, which is the ultimate goal of her efforts. 

She joined ORNL as a postdoctoral research associate in 2020 and transitioned into a scientist role in 2023 at the Computational Chemistry and Nanomaterials Sciences group within the Computational Sciences and Engineering Division in the Computing and Computational Sciences Directorate. Prior to joining ORNL, her research was primarily focused on learning about electronic properties of various functional materials using atomistic simulations combined with data-driven methods.