Stanford University
Showing 441-450 of 2,664 Results
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Sujal Dave
Postdoctoral Scholar, Cardiology
BioSujal Dave, PhD, is a Postdoctoral Scholar in the Cardiovascular Biomechanics Computation Lab at Stanford University.
He recently completed his Ph.D. in Mechanical Engineering at the University of Calgary under the supervision of Dr. Artem Korobenko, where he developed consistent reduced order modeling frameworks for turbulent flows using variational multiscale methods and stabilized finite elements. His doctoral research advanced large-scale wind turbine wake simulations with applications to renewable energy and environmental flows. -
Onja Davidson Raoelison
Postdoctoral Scholar, Economics
BioOnja Davidson Raoelison is a Postdoctoral Fellow at the King Center on Global Development. Prior to joining Stanford, she earned her PhD in Environmental Engineering from the University of California, Los Angeles. She holds a joint MSc in Civil and Environmental Engineering from UCLA and in Civil Engineering from ESTP Paris, France.
Her overarching research focuses on the connection between wildfires, the environment, and human health, aiming to develop sustainable engineering solutions to mitigate the negative impacts of wildfires on water quality. Specifically, her research agenda at the Stanford Department of Medicine aims to understand how wildfires increase the risk of infectious diseases through their impacts on the environment -
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.
