Steven R. Spurgeon

About

I am an internationally recognized materials data scientist with a 17-year track record of leveraging artificial intelligence (AI) to accelerate the discovery and design of functional materials. My expertise spans a wide range of applications, from quantum computing and microelectronics to renewable energy and national security.

Throughout my career, I have consistently led large, multidisciplinary project teams at national laboratories, resulting in over 87 publications, 6 software packages, 2 licensed technologies, an R&D 100 Award and the Microscopy Society of America Burton Medal. I have secured and managed over $2M/year in external funding and $500k/year in internal funding, driving transformative research for both basic and applied missions.

My current research focuses on developing AI-guided high-resolution imaging and spectroscopy techniques to understand the synthesis, degradation, and lifecycle of thin-film interfaces for electronics, sensing, and computing applications. I am also passionate about mentoring the next generation of scientists and engineers, and I actively participate in educational outreach programs.

Let's connect and explore how we can collaborate to advance the field of materials science through AI and data-driven innovation!

Employment

• Colorado School of Mines Joint Faculty
  2025 - Present
• University of Colorado Boulder Research Fellow
  2024 - Present
• National Laboratory of the Rockies Senior Materials Data Scientist
  2024 - Present
• Pacific Northwest National Laboratory Senior Materials Data Scientist
  2023 - 2024
• University of Washington Affiliate Associate Professor
  2022 - 2024
• Pacific Northwest National Laboratory Senior Research Scientist
  2017 - 2023
• Pacific Northwest National Laboratory Postdoctoral Research Associate
  2015 - 2017

Education

• Drexel University Ph.D. in Materials Science and Engineering
  2009 - 2014
• Carnegie Mellon University B.S. in Materials Science and Engineering
  2005 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (103)

• Balancing Autonomy and Oversight in Language-Agent-Guided Physical Experimentation
  2026 DOI: 10.21203/rs.3.rs-10671592/v1
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• Surface oxidation of refractory metals for stable oxide flux generation in molecular beam epitaxy
  Journal of Vacuum Science & Technology A 2026 DOI: 10.1116/6.0005502
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• Do We Really Need All That Data: From Data to Agency in Automated Microscopy
  Microscopy Today 2026 DOI: 10.1093/mictod/qaag035
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• Revealing the hidden third dimension of point defects in two-dimensional MXenes
  Nature Communications 2026 DOI: 10.1038/s41467-026-71670-y
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• Mechanism-Informed Breakdown: Understanding Degradation by Controlling Voltage-Hold Patterns in Proton Exchange Membrane Water Electrolyzers
  ACS Applied Energy Materials 2026 DOI: 10.1021/acsaem.5c03160
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• Revealing the evolution of order in materials microstructures using multi-modal computer vision
  npj Computational Materials 2025 DOI: 10.1038/s41524-025-01831-y
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• Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes
  2025 DOI: 10.21203/rs.3.rs-7888814/v1
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• Mind the gap: Bridging the divide between AI aspirations and the reality of autonomous microscopy
  APL Machine Learning 2025 DOI: 10.1063/5.0267699
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• Artificial intelligence for advanced functional materials: exploring current and future directions
  Journal of Physics: Materials 2025 DOI: 10.1088/2515-7639/adc29d
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• SAM-I-Am: Semantic boosting for zero-shot atomic-scale electron micrograph segmentation
  Computational Materials Science 2025 DOI: 10.1016/j.commatsci.2024.113400
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