SLAC National Accelerator Laboratory
Showing 1-20 of 90 Results
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Peter Dahlberg
Assistant Professor of Photon Science and of Structural Biology
BioPeter Dahlberg received his undergraduate degree at McGill University in 2011 and his Ph.D. in biophysics from the University of Chicago in 2016. He then came to Stanford to work with W. E. Moerner and Wah Chiu to develop correlative light and electron microscopy methods. These methods give highly specific information on the machines that fill cells and make them work. In 2021 he was awarded SLAC’s Panofsky Fellowship to continue his work on correlative microscopy. In 2023 he transitioned to a Staff Scientist role at SLAC. See the group website below for more information.
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Georgi L. Dakovski
Lead Scientist, SLAC National Accelerator Laboratory
Current Role at StanfordSince ~2016 I have been involved in the design, construction and commissioning of new instrumentation at the Linac Coherent Light Source (LCLS) at SLAC National Accelerator Laboratory, aiming at developing novel time-resolved soft x-ray scattering methods. Currently I am the Instrument Lead for the qRIXS experimental endstation, which focuses on performing resonant inelastic x-ray experiment to study ultrafast dynamics in correlated electron systems.
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Diana Gamzina
Casual - Nonexempt, SLAC National Accelerator Laboratory
Current Role at StanfordStaff Scientist
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Igor Daniel de Araujo Evangelista
Postdoctoral Scholar, Photon Science, SLAC
BioDr. Evangelista's primary research focus lies in computational modeling and theoretical analysis of semiconductor materials using advanced quantum mechanical methods, including Density Functional Theory, Quantum Monte Carlo, and ab-initio Molecular Dynamics. Evangelista investigates the electronic, structural, and mechanical properties of materials, collaborating closely with experimental groups to bridge theoretical predictions with empirical results. He is also interested in the development of empirical potentials and enhancing materials modeling through the application of machine learning techniques.
Evangelista entered the Department of Materials Science and Engineering at the University of Delaware as a Ph.D. candidate in 2018, after completing an master degree in Physics 2016-2018 at Federal Fluminense University (Brazil). Recent work includes collaborations with experimental groups to bridge theoretical predictions with empirical results, as well as applying machine learning to creating of empirical potentials to accelerate materials modeling. Evangelista has also contributed to understanding electron mobility in metal-oxide semiconductors and strain effects in two-dimensional materials. These studies showcase his expertise in electronic structure and materials design for next-generation semiconductor technologies.
