Jinchao Xu

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Jinchao Xu
partial differential equations
Scientific career
FieldsMathematics
InstitutionsPennsylvania State University
Doctoral advisorJames H. Bramble

Jinchao Xu (许进超, born 1961) is an

deep neural networks
.

Academic Biography

Xu received his bachelor's degree from the Xiangtan University in 1982, his master's degree from the Peking University in 1984, and his doctoral degree from the Cornell University in 1989. He joined the Pennsylvania State University (Penn State) in 1989 as assistant professor of mathematics, was promoted to associate professor in 1991, and to professor in 1995. He was named a Distinguished Professor of Mathematics in 2007, the Francis R. and Helen M. Pentz Professor of Science in 2010, and the Verne M. Willaman Professor of Mathematics in 2015. He is currently the director of the Center for Computational Mathematics and Applications at Penn State.

Xu serves on the editorial boards of many major journals in computational mathematics and co-edits many conference proceedings and research monographs. He also serves on various college and departmental committees and organizes numerous colloquiums and seminars. He has organized or served as a scientific committee member for more than 65 international conferences, workshops, and summer schools.

Research Interests and Contributions

Xu is an advocate of the idea that practical applications and theoretical completeness and beauty can go together. He studies numerical methods for partial differential equations and big data, especially finite element methods, multigrid methods, and deep neural networks, for their theoretical analysis, algorithmic development, and practical applications. He is well known for many groundbreaking studies in developing, designing, and analyzing fast methods for finite element discretization and for the solution of large-scale systems of equations, including several basic theories and algorithms that bear his name: the

SIAM Review paper “Iterative Methods by Space Decomposition and Subspace Correction” (1992) and more recently his Acta Numerica
paper “Algebraic Multigrid Methods” (2017).

In recent years, Xu has become interested in developing training algorithms for deep learning models and their applications, such as Alzheimer's disease, pathological image recognition, and pulse data analysis. He constructed the connections of ReLU deep neural networks and the classical linear finite element. Xu proposed a new idea for understanding ResNet models from the viewpoint of the multigrid method and also proposed iRDA training algorithms for the training process in CNN, which can achieve a sparse result in this context.

Awards and honors

Xu has published nearly 200 scientific papers and was ranked among the most highly cited mathematicians in the world by the

Hyderabad.[2] In 2011, Xu was honored as a Fellow of the Society for Industrial and Applied Mathematics (SIAM)[3] for his outstanding contributions to the theory and applications of multilevel and adaptive numerical methods. In 2012, he was elected as an inaugural Fellow of the American Mathematical Society (AMS).[4]

Xu received the Liu Memorial Award at

Humboldt Award
for Senior U.S. Scientists in 2005. He also received the Research Award for National Outstanding Youth (Class B) in 2006 in China. In 2019, Xu was named a Fellow of the American Association for the Advancement of Science(AAAS).

References

  1. ^ ICIAM conference website.
  2. ^ List of plenary and invited speakers of ICM.
  3. ^ List of SIAM fellows, class of 2011.
  4. ^ List of Fellows of the American Mathematical Society, retrieved 2013-09-01.
  5. ^ List of Feng Kang Prize winners.

External links

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