Jinchao Xu

Jinchao Xu

Xu is Professor of Applied Mathematics and Computational Sciences at KAUST, and Director of the KAUST Lab for Scientific Computing and Machine Learning. His primary research interests include the design, analysis, and application of numerical methods for scientific computing—particularly finite element and multigrid methods—as well as machine learning, including deep neural networks and large language models.

His representative contributions include pioneering theory and algorithms in multigrid and domain decomposition methods; the development of the FASP software package; the formulation of the subspace correction framework; and foundational work on the mathematics of deep learning. He has also contributed to machine learning through MgNet, which bridges ideas from numerical analysis and convolutional neural networks, and AceGPT, an LLM developed specifically for Arabic. Several influential theories and algorithms are named after him (X), including the BPX preconditioner, HX preconditioner, XZ identity, and the MWX element.

He was an invited speaker at the International Congress on Industrial and Applied Mathematics (ICIAM) in 2007 and at the International Congress of Mathematicians (ICM) in 2010. He is a Fellow of the Society for Industrial and Applied Mathematics (SIAM), the American Mathematical Society (AMS), the American Association for the Advancement of Science (AAAS), the European Academy of Sciences (EURASC), and Academia Europaea.

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  • Organization
    KAUST
  • Profession
    Professor of Applied Mathematics and Computational Sciences
Related sessions
In person
10 July 2025
14:00 - 17:00
EST - New York
CST - Beijing
PST - Los Angeles
AWST - Perth, Australia
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