Center for Computational Mathematics and its Applications
Department of Mathematics at Penn State
Nov 3-5, 2021 at The Penn Stater (Hotel & Conference Center)
Purpose. The focus of this workshop is on the development, analysis, and application of fundamental mathematical theories and advanced modeling and simulation techniques to partial differential equations (PDEs), especially using (deep) neural networks (DNN), multilevel adaptive finite element methods (FEM) and symbiosis of both. The overarching goal of this forum is to connect the communities working on numerical PDEs, neural network and machine learning, and to provide unique opportunity for collaborations and networking towards creating better and more efficient computational tools, methods and techniques for the future.
The workshop is held in honor of Jinchao Xu’s 40 years of achievements in mathematical research, and is being hosted by the Center for Computational Mathematics and Applications and the Department of Mathematics at Penn State. The scientific program for the workshop can be found [ here ]. The list of all participants is found [ here ].
Scientific and Organizing Committee
- Guest members: Long Chen (UC Irvine), Michael Holst (UC San Diego), and Xiaozhe Hu (Tufts University)
- Penn State members: Yuwen Li, Zhengqi Liu, Kelli Jones, Shawna Dougherty, Donna Cepullio, and Ludmil Zikatanov
The event is supported in part by the National Science Foundation DMS-2132710
Location. The workshop will take place in the Penn Stater Hotel and Conference Center near Penn State’s University Park Campus. Maps, directions, information about lodging, and other practical information can be found from the Practical Info tab in the menu at the top-right corner of the page.
The Fall 2021 edition of the FE circus is taking place right after this workshop at the same location. The FE circus has more than 50 years history rich in advancing research and setting traditions in computational mathematics. The website for the circus can be reached [ here ].
Contact: ludmil AT psu DOT edu