PNNL

Steven Spurgeon is a senior materials scientist at Pacific Northwest National Laboratory (PNNL) supporting the National Security Directorate. His work has resulted in dozens of journal publications, invited talks, and awards, but more recently, Spurgeon was named lead artificial intelligence (AI) and machine learning (ML) editor for the journal Microscopy and Microanalysis.

Microscopy and Microanalysis is a renowned and esteemed journal in microscopy, in the domains of physical and biological sciences. Spurgeon has been serving as an associate editor on the journal since 2022. Over the past few years, the use of AI/ML methods in almost all scientific domains has dramatically increased, and the journal has made an effort to put more emphasis in this area of research.

“Early on, I was handling a mix of research areas and domains within the journal. Now, there is an opportunity for me to focus specifically on AI/ML research in microscopy, which is important to me because I get to elevate these capabilities and it ties in nicely with my research and role at PNNL,” said Spurgeon.

Spurgeon’s long-standing involvement with the Microscopy Society of America, including contributions to journals like Microscopy and Microanalysis and Microscopy Today, combined with his extensive experience in AI/ML, uniquely qualifies him to tackle articles and organize special issues in this space.

“As applications of ML are growing at an enormous rate and since we are seeing many analyses of microscopy data based on ML and neural networks, it is fitting that we identify an editor who has strong skills in this area. I believe it is time we had an editor identified for this area and Steven is the ideal candidate. We appreciate his willingness to serve in this capacity,” said John Mansfield, Editor-in-Chief, Microscopy and Microanalysis.

Spurgeon believes that journals can ultimately shape the future of this field in a lot of ways. He is excited to not only to elevate emerging work, but to educate the next generation of scientists on these techniques and how they are being used.

Currently, Spurgeon is a joint appointee with PNNL and the University of Washington, where he serves as an affiliate associate professor in physics and takes great pride in getting students engaged in AI/ML methods. “Students are getting exposed to AI, data science, and materials science earlier in their educational career and want to know how they can make an impact. My hope and goal in this new endeavor is to educate those that are curious and show them how they can use these techniques to solve complex scientific problems,” said Spurgeon.