Marianna Safronova

Marianna Safronova is a Professor of Physics at the Department of Physics and Astronomy, University of Delaware and an Adjunct Fellow of the Joint Quantum Institute, NIST and the University of Maryland. She earned her Ph.D. in physics from the University of Notre Dame, USA in 2001. Her diverse research interests include applications of quantum technologies to search for physics beyond the standard model of elementary particles and fields, applications of quantum technologies in space, development of atomic and nuclear clocks and their applications, ultra-cold atoms and quantum information, studies of fundamental symmetries, dark matter searches, quantum many-body theory and development of high-precision relativistic atomic codes, development of the online atomic data portal, highly-charged ions, superheavy atoms, and other topics. Safronova is an author of 230 peer-reviewed publications. She and collaborators developed freely available and sustainable online data portal contributing to U.S. cyberinfrastructure ecosystem, improving usability and data access for the atomic physics, astrophysics, and plasma physics communities. She is a Fellow of the American Physical Society and 2018-2019 Chair of American Physical Society Division of the Atomic, Molecular, and Optical Physics. Learn more at https://www.mariannasafronova.com.

Marianna Safronova was elected a fellow of the American Physical Society (APS) in 2011 for innovative development of high-accuracy first-principles methods of computational atomic structure and dynamics, and their application to optical atomic clocks, quantum computing with neutral atoms, and tests of fundamental symmetries. She was nominated by the Division of Atomic, Molecular and Optical Physics.

She received the 2000 SGI Award for Excellence in Computational Sciences and Visualization at the University of Notre Dame for work Parity Nonconservation in Atomic Francium. This award recognizes outstanding contributions by a graduate student in the areas of computational sciences and visualization.