The Peter Duncumb Award for Excellence in Microanalysis recognizes outstanding achievement by a currently active individual over a sustained period of time in the field of microanalysis through technical accomplishment, leadership, educational, and professional activities. The award is sponsored by MAS Sustaining Member Bruker Nano Inc.
Dr. Kalinin is a world-renowned microscopist at the forefront of artificial intelligence and machine learning methods for microanalysis and atomic-level manipulation of materials. Originally hailing from Moscow, Russia, he earned his Ph.D. in 2002 at the University of Pennsylvania in the laboratory of Dr. Dawn Bonnell. He moved to Oak Ridge National Laboratory (ORNL) as a Eugene Wigner Fellow and worked there for 20 years, eventually being promoted to Corporate Fellow (the highest recognition bestowed upon research staff at ORNL) and leading a new Data Analytics group. He was also Director of the Institute for Functional Imaging of Materials at ORNL from 2014–2019. While at ORNL, Dr. Kalinin found that typical approaches for analyzing microscopy data, based on classical models or simple image analytics, were limited in scope. He was an early adopter of artificial neural networks to analyze hyperspectral datasets and identify specific features in scanning probe microscopy (SPM) and scanning transmission electron microscopy (STEM) datasets. This allowed for the rapid identification of correlations between local microstructure and spectral features in real time. He continued to develop this machine learning approach to be technique-agnostic, so that it could be applied to almost any microscopy dataset. Soon, Dr. Kalinin and other researchers were implementing machine learning models to drive artificial intelligence control for automated microscopy. “This is a significant shift from the traditional paradigm where human operators guide the experiment, often leading to biases and missed information,” said Dr. Steve Spurgeon, who develops AI software for TEM based on Dr. Kalinin’s concepts. Dr. Kalinin has also developed a framework for atomic-level fabrication that promises a future where nanoscale assemblies are constructed atom-by-atom in the electron microscope. “Sergei undeniably is leaving an enduring imprint on the dynamic landscape of this transformative discipline,” said fellow colleague and collaborator, Dr. Ray Unocic.
In addition to these technical achievements, Dr. Kalinin is committed to democratizing data science for materials research. He strives to make data and code freely available and adheres to FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles. He recently started a free, virtual summer school for artificial intelligence and machine learning in electron microscopy. His ability to communicate and understand both physical science and machine learning fields led to a year as a principal scientist at the Amazon Grand Challenge Moonshots Factory Lab in 2022. He has received the Burton Medal from MSA, the Medard Welch Award from the American Vacuum Society, the Blavatnik Award for Physical Sciences, and the Feynman Experimental Prize from the Foresight Institute. Dr. Kalinin is currently the Weston Fulton Professor of Materials Science and Engineering at the University of Tennessee, Knoxville and Chief Scientist of Artificial Intelligence and Machine Learning for Physical Sciences at Pacific Northwest National Laboratory.