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George Em Karniadakis

Affiliations:	1988-1993	Mechanical and Aerospace Engineering	Princeton University, Princeton, NJ
	1994-		Brown University, Providence, RI

Area:

Fluid and Plasma Physics, Mathematics

Website:

https://www.brown.edu/research/projects/crunch/george-karniadakis

Google:

"George Em Karniadakis" OR "George E Karniadakis"

Bio:

https://www.brown.edu/research/projects/crunch/sites/brown.edu.research.projects.crunch/files/uploads/PGEK_Resume.pdf
https://www.brown.edu/research/projects/crunch/sites/brown.edu.research.projects.crunch/files/uploads/Karniadakis_2017.pdf
https://www.researchgate.net/profile/George-Karniadakis
https://scholar.google.com/citations?user=yZ0-ywkAAAAJ&hl=en

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Parents

Borivoje B. Mikic	grad student	1987	MIT (BME Tree)
Anthony T. Patera	grad student	1987	MIT (E-Tree)
(The Spectral Element Method Applied to Heat Transfer Enhancement by Flow Destabilization)

Children

Ali Beskok	grad student	1996	Princeton (Physics Tree)
Timothy Warburton	grad student	1993-1998	Brown
Yiqing Du	grad student	2000	Brown
HsinChih F. Liu	grad student	2000	Brown (Physics Tree)
Haralabos Marmanis	grad student	2000	Brown
Xia Ma	grad student	2001	Brown
Didier Lucor	grad student	2004	Brown
Dongbin Xiu	grad student	2004	Brown
Sirod Sirisup	grad student	2005	Brown
Igor V. Pivkin	grad student	2006	Brown
Vasileios Symeonidis	grad student	2006	Brown
Guang Lin	grad student	2007	Brown
Xiaoliang Wan	grad student	2007	Brown
Leopold Grindberg	grad student	2009	Brown
Xian Luo	grad student	2009	Brown
Hyoungsu Baek	grad student	2010	Brown
Dmitry A. Fedosov	grad student	2010	Brown

Collaborators

BETA: Related publications

Publications

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Kharazmi E, Cai M, Zheng X, et al. (2021) Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks. Nature Computational Science. 1: 744-753
Zhang S, Ponce J, Zhang Z, et al. (2021) An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City. Plos Computational Biology. 17: e1009334
Song F, Karniadakis GE. (2021) Variable-Order Fractional Models for Wall-Bounded Turbulent Flows. Entropy (Basel, Switzerland). 23
Li H, Sampani K, Zheng X, et al. (2020) Predictive modelling of thrombus formation in diabetic retinal microaneurysms. Royal Society Open Science. 7: 201102
Jin P, Zhang Z, Zhu A, et al. (2020) SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems. Neural Networks : the Official Journal of the International Neural Network Society. 132: 166-179
Deng Y, Papageorgiou DP, Li X, et al. (2020) Quantifying Fibrinogen-Dependent Aggregation of Red Blood Cells in Type 2 Diabetes Mellitus. Biophysical Journal
Zheng X, Yazdani A, Li H, et al. (2020) A three-dimensional phase-field model for multiscale modeling of thrombus biomechanics in blood vessels. Plos Computational Biology. 16: e1007709
Lu L, Dao M, Kumar P, et al. (2020) Extraction of mechanical properties of materials through deep learning from instrumented indentation. Proceedings of the National Academy of Sciences of the United States of America
Raissi M, Yazdani A, Karniadakis GE. (2020) Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations. Science (New York, N.Y.)
Zhang D, Guo L, Karniadakis GE. (2020) Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks Siam Journal On Scientific Computing. 42: A639-A665

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