George Karniadakis

George Em Karniadakis (Γιώργος Εμμανουήλ Καρνιαδάκης) is the Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics at Brown University.[1] He is a Greek-American researcher who is known for his wide-spectrum work on high-dimensional stochastic modeling and multiscale simulations of physical and biological systems. He is one of the pioneers of spectral/hp-element methods for fluids in complex geometries, general Polynomial Chaos for uncertainty quantification, and the theory of Sturm-Liouville theory for partial differential equations and fractional calculus.

George Em Karniadakis
George Em Karniadakis
Born
Crete, Greece
Nationality Greece- United States
Scientific career
FieldsApplied mathematics, Mechanical Engineering, Ocean Engineering
InstitutionsBrown University, Massachusetts Institute of Technology
Doctoral advisorAnthony T. Patera
Borivoje B. Mikic

His current research interests are on machine learning for scientific computing (Scientific Machine Learning), that is how to solve and discover new PDEs via deep learning, hence removing the tyranny of grids and using gappy data only. Current thrusts include probabilistic numerics, stochastic simulation (in the context of uncertainty quantification and beyond), fractional PDEs, and multiscale modeling of complex systems.

He has advised more than fifty (50+) PhD students in diverse areas of research including physics-informed machine learning, numerical analysis for fractional PDEs, stochastic PDEs, modeling uncertainty with polynomial chaos, multiscale modeling of biological systems, dissipative particle dynamics, flow-structure interactions, numerical methods for computational fluid dynamics, parallel computing, and interactive/virtual reality computer graphics.

Biography

George Em Karniadakis obtained his diploma (honors) of engineering in Mechanical Engineering and Naval Architecture from the National Technical University of Athens in 1982. Subsequently, he received his S.M. in 1984 and his Ph.D. in Mechanical Engineering and Applied Mathematics in 1987 from Massachusetts Institute of Technology under the advice of Anthony T. Patera and Borivoje B. Mikic. Then, he joined the Center for Turbulence Research at Stanford University, NASA Ames Laboratory, as a postdoctoral research associate under the mentorship of Parviz Moin and John Kim . In 1988, he joined Princeton University as a tenure-track assistant professor in the department of Mechanical and Aerospace Engineering also as an associate faculty in the Program of Applied and Computational Mathematics (PACM). In 1993, he held a visiting professor appointment in the Aeronautics Department at California Institute of Technology. Then, he joined the Division of Applied Mathematics at Brown University as a tenured associate professor in 1994. He became a full professor of Applied Mathematics in 1996. Since 2000, he has been also a visiting professor and senior lecturer of Ocean/Mechanical Engineering at Massachusetts Institute of Technology.[2] He was entitled the Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics in 2014.

He is currently the lead PI of an OSD/ARO/MURI on Fractional PDEs, and currently the lead PI of an OSD/AFOSR MURI on Machine Learning for PDEs.  He is also the Director of the DOE center PhILMS on Physics-Informed Learning Machines and previously he was also the Director of  the DOE Center of Mathematics for Mesoscale Modeling of Materials (CM4).

Honors and Awards
  • SIAM/ACM Prize in Computational Science and Engineering, 2021.
  • American Association for the Advancement of Science (AAAS) Fellow, 2019.
  • Alexander von Humboldt award, 2017.
  • Ralph E. Kleinman Prize, Society for Industrial and Applied Mathematics, 2015[3]
  • MCS Wiederhielm Award of the Microcirculatory Society "for the most highly cited original article in Microcirculation over the previous five year period for the paper", 2015[1]
  • US Association for Computational Mechanics, 2013, The J Tinsley Oden (inaugural) Medal.[4]
  • US Association for Computational Mechanics, 2007 Computational Fluid Dynamics award.[5]
  • Fellow of the Society for Applied and Industrial Mathematics (SIAM), 2010.[6]
  • Fellow of the American Physical Society (APS), 2004.[7]
  • Fellow of the American Society of Mechanical Engineers (ASME), 2003.[8]
  • Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA), 2006.[9]

Research Accomplishments
  • Development of physics-informed learning machines – deep learning
  • Fractional Sturm-Liouville theory and first three-dimensional realistic simulations using fractional PDEs.
  • Development of generalized Polynomial Chaos and Uncertainty Quantification.
  • First simulation of the human arterial tree on the Teragrid.
  • Development of generalized polynomial chaos methods for modeling uncertainty in unsteady flows.
  • First direct (DNS) and large-eddy simulation (LES) of turbulence in complex geometries.
  • First theoretical/numerical work on gas micro-flows.
  • Discovery of secondary instability/transition in wake flows.
  • Discovery of a new drag reduction technique using electromagnetic forcing (two patents).
  • Development of high-order methods on unstructured meshes.
  • Development of high-order discontinuous Galerkin methods for compressible/supersonic flows.
  • Development of a new expansion basis: Singular Stokes eigenfunctions.
  • Work featured on the covers of: Physics Today (March 1993); Parity (Japanese -November 1993); Scientific Computing & Automation (June 1994), MHPCC’97 (November 1997), ACCESS/NCSA (November 1998), Cover of Book on “Recent Advances in DNS and LES” (Kluwer, 1999); work featured in Science and reports in New Scientist, Industrial Physicist, and several popular magazines/newspapers around the world; Aerospace America 2001; NCSA Access 2002 and on Power Wall in SC’02, cover of Phys. Rev. Lett. (2004); NCSA Access 2006; Biophysics J, 2017.

Books

1. Z. Zhang and G.E. Karniadakis, “Numerical Methods for Stochastic PDEs with White Noise”, Springer, Applied Mathematics Series, 2017.

2. G.E. Karniadakis, A. Beskok and N. Aluru, “Microflows and Nanoflows: Fundamentals and Simulation, Springer 2005.

3. G.E. Karniadakis and R.M. Kirby, “Parallel Scientific Computing in C++ and MPI”, Cambridge University Press, March 2003.

4. G.E. Karniadakis and A. Beskok, “Microflows: Fundamentals and Simulation”, Springer, 2001. (first textbook/monograph in this field).

5. G.E. Karniadakis & S.J. Sherwin, “Spectral/hp Element Methods for CFD,” Oxford University Press, New York, 1999. (first monograph in this field); second edition, Oxford, 2005; third edition, 2013.

Patents

1. S. Suresh, L. Lu, M. Dao and G.E. Karniadakis, “Solving inverse indentation Problems via Deep Learning with Applications to 3D printing and Other Engineering Projects, (NTU Ref: 2019-140) - June 24, 2019.

2. M. Raissi, P. Perdikaris and G.E. Karniadakis, Physics Informed Learning Machines U.S. Provisional Patent Application 6248319, March 29, 2017.

3. G.E. Karniadakis and Y. Du, “Method and Apparatus for Reducing Turbulent Drag”, Patent No. 6,333,593 B1, Dec 25, 2001.

4. G.E. Karniadakis, K. Breuer and V. Symeonidis, “Method and Apparatus for Reducing Turbulent Drag (continuing part)”, Patent No. 6,520,455 B2, Feb. 18, 2003.

5. C. Chryssostomidis, D. Sura, G.E. Karniadakis, C. Jaskolski, R. Kimbal, “Lorentz Acoustic Transmitter for Underwater Communications”, Patent No. 7,505,365, March 17, 2009.

Consulting Experience

Cooling of electronic components (AT & T Bell Labs, Fujitsu Ltd.), modeling of heat exchange in automobiles (GM Corp.), unsteady piston flows (CTI-Cryogenics), flow through pumps (EDO Co.), design of novel aluminum furnaces (ALCAN Can. Labs), mass transfer in paper-making (Union Camp), combustion (Sandia Labs), noise prediction and jet flows (AeroChem Labs, Inc.), crystal growth (G.E. Co.), bio-fluids (Allied), boiler fouling (AVCO Res. Labs), prediction of by-pass transition (NASA Lewis), applied numerical methods (Nuclear Regulatory Commission), flow-structure interactions (Norsk Hydro), Ocean Power Technology (energy-harvesting eel), Chevron (modeling of risers), PCMC, Inc. (microfluidics/turbulence), United Technologies (uncertainty quantification), DeepStar (vortex-induced vibrations of risers).

Editorial Service

- Associate Editor of Journal of Computational Physics, 2006-;

- Associate Editor of Biomechanics and Modeling in Mechanobiology.

- Associate Editor of Calcolo, 2015-2018;

- Associate Editor of SIAM Journal on Scientific Computing, 2017-;

- Associate Editor of SIAM Reviews, 2017-

- Associate Editor of SIAM J. Uncertainty Quantification, 2018-

- Associate Editor of Mathematical Models and Methods in Applied Sciences, 2017- 2018:

- Associate Editor of Acta Mechanica Sinica, 2004 -;

- Associate Editor of J. Fluids Engineering, 1993-96; 2000-2003;

References
  1. Stacey, Kevin (March 26, 2015). "Karniadakis wins two professional awards". News from Brown. Brown University.
  2. "George Em Karniadakis". Retrieved September 12, 2019.
  3. "Karniadakis Earns 2015 Ralph E. Kleinman Prize". Pacific Northwest National Laboratory. March 2015. Retrieved 2019-09-12.
  4. http://www.usacm.org/usacm_new_award
  5. Award recipients, US Association for Computational Mechanics, retrieved 2015-04-21.
  6. SIAM Fellows class of 2010, retrieved 2019-09-12.
  7. APS Fellow listing, retrieved 2019-09-12.
  8. Plenary speaker biography, ASME 2013 Fluids Engineering Division Summer Meeting, retrieved 2015-04-21.
  9. AIAA Associate Fellows roster, retrieved 2015-04-21.
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