Elias Massoud is a research scientist in the Integrated Computational Earth Science (ICES) Group within the Computational Sciences and Engineering Division at Oak Ridge National Laboratory, which he joined in 2022. His scientific focus centers on model-data integration, leveraging advanced Bayesian statistics alongside artificial intelligence and machine learning to bridge computer simulations and observational data. A key pillar of his methodology is benchmarking and evaluation of Earth system models, which involves curating complex datasets, designing diagnostic frameworks, and evaluating performance metrics to pinpoint where models succeed and where they require refinement.
Elias applies these approaches across several research initiatives. Through the RUBISCO project, he utilizes hybrid computational methods to advance the predictive skill of land models. He also supports the Earth System Grid Federation (ESGF2-US) initiative, facilitating broader and more accessible data discovery for the global Earth science community. Additionally, he contributes to NGEE Arctic by investigating complex ecosystem dynamics across multiple scales in remote northern environments. Beyond modeling and benchmarking, he develops innovative model-weighting frameworks designed to combine information on Earth system processes for regional and national assessments.
Before coming to ORNL, Elias held research positions at the University of California, Berkeley, and NASA’s Jet Propulsion Laboratory. He earned his undergraduate and graduate degrees from the University of California, Los Angeles (’11, ’12) and the University of California, Irvine (’17).
