Director, PhILMs
Joint Appointment, Computational Math Group
Director, PhILMs
Joint Appointment, Computational Math Group


George Karniadakis holds a joint appointment in PNNL’s Computational Math Group. As a part of his appointment, he is the director of the Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PhILMs) collaboratory led by PNNL. He is also the Charles Pitts Robinson and John Palmer Barstow professor of Applied Mathematics and Engineering at Brown University.

A native of Crete, Karniadakis studied mechanical engineering and naval architecture at the National Technical University of Athens, Greece. He received his master’s and PhD degrees from Massachusetts Institute of Technology (MIT) in 1984 and 1987, respectively, where he was appointed lecturer in the Department of Mechanical Engineering. He subsequently joined the Center for Turbulence Research at Stanford University / NASA Ames. Karniadakis also joined Princeton University as an assistant professor in the Department of Mechanical and Aerospace Engineering and as an associate faculty member in the Program of Applied and Computational Mathematics. He was a visiting professor at Caltech in 1993, in the Aeronautics Department and joined Brown University as an associate professor of Applied Mathematics in the Center for Fluid Mechanics in 1994.

Karniadakis has held a joint appointment at PNNL since 2013. He has been a full professor at Brown University since 1996, and a visiting professor and senior lecturer of Ocean/Mechanical Engineering at MIT since 2000. He has also served twice as a visiting professor at Peking University. His research interests include diverse topics in computational science on both algorithms and applications.

Disciplines and Skills

  • Applied Mathematics
  • Mechanical and Aerospace Engineering
  • Computational Mathematics
  • Scientific Machine Learning


  • PhD in Mechanical Engineering, Minor in Applied Mathematics, MIT, Cambridge, 1987
  • MS in Mechanical Engineering, MIT, Cambridge, 1984 (Bodossaki Foundation Fellow)
  • BS in Mechanical Engineering and Naval Architecture, National Technical University of Athens, 1982 (Honors)

Affiliations and Professional Service

  • Charles Pitts Robinson and John Palmer Barstow Professor, Brown University, Applied Mathematics and Engineering, and PNNL Research Scientist (part time, 2012 – present)
  • Visiting Professor/Senior Lecturer/Research Scientist, MIT, Ocean/Mechanical Engineering (Sept. 2000 – present)
  • Professor, Division of Applied Mathematics, Brown University (July 1996 – 2013)
  • Visiting Professor, Peking University (2007 and 2013)
  • Associate Professor, Division of Applied Mathematics, Brown University (Jan. 1994 – June 1996)
  • Visiting Professor, College of Engineering, Peking University (Fall quarters 2007 and 2013)
  • Visiting Professor, Department of Aeronautics and Applied Mathematics, Caltech (Spring quarter 1993)
  • Assistant Professor, Department of Mechanical and Aerospace Engineering; also Associate Faculty, Program in Applied and Computational Mathematics, Princeton University (Sept. 1988 – Dec. 1993)
  • Research Associate, MIT; Advisor: AT Patera (April 1988 – Aug. 1988)
  • Research Fellow, Center for Turbulence Research, Stanford University / NASA Ames (Sept. 1987 – March 1988)
  • Research Center; Advisors: P Moin and J Kim
  • Lecturer, Department of Mechanical Engineering, MIT (June 1987 – Aug. 1987)
  • Research Assistant, MIT; Advisors: AT Patera and BB Mikic (July 1984 – May 1987)
  • Research Assistant, MIT; Advisor: W Unkel (Jan. 1983 – June 1984)
  • Research Assistant, National Technical University of Athens; Advisor: T Loukakis (June 1982 – Dec. 1982)

Awards and Recognitions

  • Society for Industrial and Applied Mathematics/Association of Computing Machinery (SIAM/ACM) Prize in Computational Science and Engineering (2021)
  • American Association for the Advancement of Science (AAAS) Fellow (2019)
  • Alexander von Humboldt Fellow (2017)
  • SIAM Computational Science and Engineering, best poster Award (2017)
  • International Conference on Fractional Differentiation and its Applications (ICFDA)’16 Riemann-Liouville Award (2016)
  • ICMMES-MDPI best poster Award, 13th International Conference for Mesoscopic Methods in Engineering and Science-Multidisciplinary Digital Publishing Institute (2016)
  • SIAM Ralph E. Kleinman Prize (2015)
  • Wierderhielm Award, most cited original paper in “Microcirculation” for five years (2015)
  • U.S. Association of Computational Mechanics, J Tinsley Oden Medal (2013)
  • Fellow of the Society for Applied and Industrial Mathematics (2010)
  • U.S. Association of Computational Mechanics, Computational Fluid Dynamics Award (2007)
  • Associate Fellow of the American Institute of Aeronautics and Astronautics (2006)
  • Fellow of the American Physical Society (2004)
  • Fellow of the American Society of Mechanical Engineers (2003)
  • 17th Robert Bruce Wallace Lecture award, MIT (2003)
  • Rheinstein Junior Faculty Award, Princeton University (1992)
  • U.S. Department of Energy/Scientific Discovery through Advanced Computing (SciDAC) program Visualization Award, with Argonne National Laboratory researchers (2011)
  • Finalist, Gordon Bell Prize, Supercomputing’15, with Koumoutsakos et al. (2015)
  • Finalist, Gordon Bell Prize, Supercomputing’11, with Grinberg, Morozov et al. (2011)
  • Best poster in Supercomputing’08 (with L Grinberg, J Cazes) on “A Scalable Domain Decomposition (2008)
  • Method for Ultra-Parallel Arterial Flow Simulation, Supercomputing’08, Austin (2008)


  • NTU Ref: 2019-140, Suresh S, L Lu, M Dao, and GE Karniadakis. June 24, 2019. “Solving inverse indentation Problems via Deep Learning with Applications to 3D printing and Other Engineering Projects.”
  • Raissi M, P Perdikaris, and GE Karniadakis. March 29, 2017. “Physics-Informed Learning Machines.” U.S. Provisional Patent Application No. 6,248,319.
  • Chryssostomidis C, D Sura, GE Karniadakis, C Jaskolski, and R Kimbal, March 17, 2009. “Lorentz Acoustic Transmitter for Underwater Communications.” U.S. Patent No. 7,505,365.
  • Karniadakis GE, K Breuer, and V Symeonidis. February 18, 2003, “Method and Apparatus for Reducing Turbulent Drag (continuing part).” U.S. Patent No. 6,520,455, B2.
  • Karniadakis GE and Y Du. December 25, 2001. “Method and Apparatus for Reducing Turbulent Drag.” U.S. Patent No. 6,333,593, B1.


To view a complete list of Dr. Karniadakis’ publications, visit


  • Yang L, X Meng, and GE Karniadakis. 2021. "B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data." Journal of Computational Physics 425:109913. PNNL-SA-158354. doi:10.1016/


  • Jagtap A, K Kawaguchi, and GE Karniadakis. 2020. "Adaptive activation functions accelerate convergence in deep and physics-informed neural networks." Journal of Computational Physics 404:109136. PNNL-SA-152708. doi:10.1016/
  • Lu L, M Dao, P Kumar, U Ramamurtyc, GE Karniadakis, and S Suresh. 2020. "Extraction of mechanical properties of materials through deep learning from instrumented indentation." Proceedings of the National Academy of Sciences (PNAS). 117(13):7052-7062. PNNL-SA-152699. doi:10.1073/pnas.1922210117.
  • Meng X and GE Karniadakis. 2020. "A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems." Journal of Computational Physics 401:109020. PNNL-SA-152903. doi:10.1016/
  • Raissi M, A Yazdani, and GE Karniadakis. 2020. "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations." Science 367(6481):1026-1030. PNNL-SA-152906. doi:10.1126/science.aaw4741.


  • Alber M, A Buganza Tepole, WR Cannon, S De, S Dura-Bernal, K Garikipati, and GE Karniadakis, et al. 2019. "Integrating machine learning and multiscale modeling – perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences." npj Digital Medicine 2:115. PNNL-SA-147139. doi:10.1038/s41746-019-0193-y.
  • Blumers AL, Z Li, and GE Karniadakis. 2019. "Supervised parallel-in-time algorithm for long-time Lagrangian simulations of stochastic dynamics: Application to hydrodynamics." Journal of Computational Physics 393:214-228. PNNL-SA-151156. doi:10.1016/
  • Wang Y, Z Li, J Xu, C Yang, and GE Karniadakis. 2019. "Concurrent coupling of atomistic simulation and mesoscopic hydrodynamics for flows over soft multi-functional surfaces." Soft Matter 15(8):1747-1757. PNNL-SA-151287. doi:10.1039/c8sm02170h.