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Francesca Tavazza (Fed)

Group Leader

Francesca Tavazza has been a member of the scientific staff at the National Institute of Standards and Technology (NIST) since 2003. She earned an undergraduate degree in Physics and a MS in Materials Science from Universita’ Statale di Milano, Italy, and a PhD in Physics from the University of Georgia. She is currently leading the Materials for Energy and Sustainable Development Group in the Materials Measurement Science Division, with focus on autonomous design and machine learning (ML) applied to materials design and characterization. Before, she served as Project Leader of the “Electronic and Functional Materials” project, leading a team focused on computational modeling, high-throughput discovery, and AI/ML investigation of solid-state material properties. Her areas of expertise include Density Functional Theory (DFT) modeling of quantum phenomena, electronic, optical and spectroscopic properties of standard and van der Waals-bonded materials, DFT and Molecular Dynamics investigation of mechanical deformations, uncertainty evaluation in DFT and ML, fitting of force fields and ML models. She has published over a hundred papers in refereed journals and contributed to the organization of tens of workshops/symposia. She served as chair of the Computational Materials Science and Engineering committee, TMS, in 2020-2022, as well as is part of the TMS Materials Innovation Committee - subcommittee on AI. 


AI for Materials

Debra Audus, Kamal Choudhary, Brian DeCost, A. Gilad Kusne, Francesca Tavazza, James A. Warren
The application of artificial intelligence (AI) methods to materials re- search and development (MR&D) is poised to radically reshape how materials are
Created October 9, 2019, Updated March 27, 2023