Dr. Giulia Galli
Liew Family Professor, Institute for Molecular Engineering
University of Chicago
"Materials discovery and scientific design by computation: what does it take?"
Abstract: Substantial progress has been made in the last three decades in understanding and predicting the fundamental properties of materials and molecular systems from first principles, employing electronic structure methods and atomistic simulations. Using specific examples, I will discuss some of the major challenges involved in enabling scientific discoveries by computation; in particular I will touch upon theoretical validation; and collection, verification and use of data generated by simulations. I will also discuss some of the theoretical and algorithmic advances required to broaden the scope of properties accessible by current ab initio simulations.
Bio: Giulia Galli is the Liew Family professor of Electronic Structure and Simulations in the Institute for Molecular Engineering at the University of Chicago. She also holds a Senior Scientist position at Argonne National Laboratory (ANL) and she is a Senior Fellow of the UChicago/ANL Computational Institute. Prior to joining UChicago and ANL, she was Professor of Chemistry and Physics at UCDavis (2005-2013) and the head of the Quantum Simulations group at the Lawrence Livermore National Laboratory (1998-2005). She holds a Ph.D. in Physics from the International School of Advanced Studies (SISSA) in Trieste, Italy. She is a Fellow of the American Physical Society (APS) and of the AAAS. She is the recipient of an award of excellence from the Department of Energy (2000) and of the Science and Technology Award from the Lawrence Livermore National Laboratory (2004). She served as chair of the Extreme Physics and Chemistry of Carbon Directorate of the Deep Carbon Observatory (DCO) in 2010-2013 and she is currently the director of MICCoM (Midwest Integrated Center for Computational Materials), established by DOE in 2015. Her research activity is focused on the development and use of theoretical and computational tools to understand and predict the properties and behavior of materials (solids, liquids and nanostructures) from first principles.
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