PNNL

Davis Brown is a data scientist in Pacific Northwest National Laboratory’s (PNNL) National Security Directorate on the Mathematics of Data Science team. He has broad interest in machine learning and works on deep learning interpretability and trustworthiness, as well as using machine learning to better understand material science and other scientific problems. Application domains have ranged from remote sensing to natural language processing.

Davis is principal investigator for the Mathematics for Artificial Reasoning in Science initiative project Artificial Intelligence with Concepts (AIwC): Leveraging Domain Concepts for Explainable and Revisable AI, which uses scientific domain concepts to better understand and modify neural networks. Davis received a BS in physics from the University of North Carolina at Chapel Hill in 2020 as a Morehead-Cain Scholar and previously worked as a data scientist for a few start-ups.