Biography:
Dr. Chan is a scientist at the Center for Nanoscale Materials at Argonne National Laboratory who studies nanomaterials and renewable energy materials, including solar cells, batteries, thermoelectrics, and catalysts. Her particular focus is on using artificial intelligence/machine learning (AI/ML) for efficient materials property prediction and for interfacing modeling with x-ray, electron, and scanning probe characterization. She also works on using AI for extracting microscopy and spectroscopy data from scientific literature and for microscopy data management.
Chan is a senior fellow at the Northwestern Argonne Institute for Science and Engineering, and a fellow of the University of Chicago Consortium for Advanced Science and Engineering. She is an associate editor at the ACS Journal Chemistry of Materials, a member of the Condensed Matter and Materials Research Committee of the National Academies of Sciences, and serves on the advisory boards for the journal APL-Machine Learning, Duke’s aiM-NRT AI training project, and CEDARSEFRC. She was elected a Fellow of the American Physical Society in 2024. (Source)
