Summary
Steven Spurgeon is a Senior Materials Data Scientist based in Golden, Colorado, who combines 17 years of materials research with a decade of applied experience in AI-guided materials discovery. He leads autonomous materials science programs across national labs and academia, serving as co-PI on a $14M DOE EFRC and PI on multi-hundred-thousand-dollar LDRD projects focused on thin-film interfaces and power electronics. Steven’s work spans from hands-on aberration-corrected STEM and correlative atomic-scale imaging to deploying sparse-data and control-theory approaches for automated experimentation, yielding over 79 publications, multiple software packages, and licensed technologies. He has been recognized with an R&D 100 Award and the Microscopy Society of America’s Burton Medal, and he frequently bridges lab-to-region partnerships through faculty and consulting roles. Notably, he has built interdisciplinary programs that operationalize autonomous learning at the edge, accelerating discovery workflows for energy, sensing, and quantum materials. His blend of deep microscopy expertise, funded leadership, and engineering of autonomous experiments makes him a go-to leader for turning complex materials science challenges into operationalized, AI-driven pipelines.
10 years of coding experience
20 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Materials Science and Engineering, Doctor of Philosophy (Ph.D.) Materials Science and Engineering at Drexel University
Bachelor of Science Materials Science and Engineering, Bachelor of Science Materials Science and Engineering at Carnegie Mellon University