George Karniadakis received the Society for Industrial and Applied Mathematics (SIAM) prize for his contributions to computational science and engineering. SIAM and the Association for Computing Machinery (ACM) jointly award the Prize in Computational Science and Engineering every two years at the SIAM Conference. The award recognizes outstanding contributions to the development and use of mathematical and computational tools and methods for the solution of science and engineering problems.
Karniadakis holds a joint appointment in the Computational Math Group at Pacific Northwest National Laboratory (PNNL) and is the Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and Engineering at Brown University. 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.
The prize was awarded to Karniadakis in March 2021 for “advancing spectral elements, reduced-order modeling, uncertainty quantification, dissipative particle dynamics, fractional partial differential equations and scientific machine learning, while pushing applications to extreme computational scales and mentoring many leaders.”
In an interview with SIAM, Karniadakis said he was grateful to receive the SIAM/ACM prize “after 30 years of developing computational methods to solve multiscale real-world problems.”
Karniadakis presented a virtual lecture at the SIAM Conference titled “DeepONet: Learning Linear, Nonlinear and Multiscale Operators Using Deep Neural Networks Based on the Universal Approximation Theorem of Operators” on Friday, March 5, 2021.
To learn more about the 2021 SIAM Conference, visit the SIAM Conference webpage here.