World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
68
Citations
18931
World Ranking
311
National Ranking
172

Engineering and Technology

D-Index
69
Citations
19416
World Ranking
1122
National Ranking
376

Research.com Recognitions

  • 2019 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2013 - Fellow of the American Mathematical Society
  • 2011 - SIAM Fellow For contributions to the theory and applications of multilevel and adaptive numerical methods.

Overview

Jinchao Xu is a researcher affiliated with Pennsylvania State University in the United States. Their work spans multiple areas within computer science and engineering, with significant contributions to artificial intelligence and computational mechanics.

Their recent publications include diverse topics ranging from applied computational methods to theoretical aspects of neural networks. Notable recent papers are:

  • Flexible sensing enabled packaging performance optimization system (FS-PPOS) for lamb loss reduction control in E-commerce supply chain, 2022, Food Control
  • Finite Neuron Method and Convergence Analysis, 2020, Communications in Computational Physics

Jinchao Xu collaborates frequently with several other researchers. Key co-authors include Qingguo Hong, Jonathan W. Siegel, Juncai He, Limin Ma, and Long-Qing Chen.

The main fields of study for this researcher are:

  • Computer Science
  • Engineering

Within these broad areas, specific subfields where they focus their research are:

  • Artificial Intelligence
  • Computational Mechanics
  • Statistical and Nonlinear Physics
  • Electrical and Electronic Engineering
  • Numerical Analysis

Their publications often appear in the following venues, indicating active engagement with the scientific community across multiple platforms:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Communications in Computational Physics
  • Journal of Computational Physics
  • Mathematics of Computation

Their research covers numerous main topics, reflecting an intersection of theoretical and applied science:

  • Neural Networks and Applications
  • Advanced Numerical Methods in Computational Mathematics
  • Model Reduction and Neural Networks
  • Stochastic Gradient Optimization Techniques
  • Electromagnetic Simulation and Numerical Methods
  • Numerical methods for differential equations
  • Numerical methods in engineering

Awards recognizing their contributions include:

  • Fellow of the American Association for the Advancement of Science (AAAS), 2019
  • Fellow of the American Mathematical Society, 2013
  • SIAM Fellow, 2011, for contributions to the theory and applications of multilevel and adaptive numerical methods

Best Publications

  • Iterative methods by space decomposition and subspace correction

    Jinchao Xu

  • Parallel multilevel preconditioners

    James H. Bramble;Joseph E. Pasciak;Jinchao Xu

  • Two-grid Discretization Techniques for Linear and Nonlinear PDEs

    Jinchao Xu

  • A novel two-grid method for semilinear elliptic equations

    Jinchao Xu

  • Nodal Auxiliary Space Preconditioning in H(curl) and H(div) Spaces

    Ralf Hiptmair;Jinchao Xu

  • Convergence estimates for multigrid algorithms without regularity assumptions

    James H. Bramble;Joseph E. Pasciak;Jun Ping Wang;Jinchao Xu

  • Convergence estimates for product iterative methods with applications to domain decomposition

    James H. Bramble;Joseph E. Pasciak;Jun Ping Wang;Jinchao Xu

  • A monotone finite element scheme for convection-diffusion equations

    Jinchao Xu;Ludmil Zikatanov

  • The analysis of multigrid algorithms with nonnested spaces or noninherited quadratic forms

    James H. Bramble;Joseph E. Pasciak;Jinchao Xu

  • Some Estimates for a Weighted L 2 Projection

    James H. Bramble;Jinchao Xu

  • A Two-Grid Method of a Mixed Stokes-Darcy Model for Coupling Fluid Flow with Porous Media Flow

    Mo Mu;Jinchao Xu

  • Some Nonoverlapping Domain Decomposition Methods

    Jinchao Xu;Jun Zou

  • The method of alternating projections and the method of subspace corrections in Hilbert space

    Jinchao Xu;Ludmil Zikatanov

  • A two-grid discretization scheme for eigenvalue problems

    Jinchao Xu;Aihui Zhou

  • Some observations on Babu s}ka and Brezzi theories

    Jinchao Xu;Ludmil Tomov Zikatanov

  • Local and parallel finite element algorithms based on two-grid discretizations

    Jinchao Xu;Aihui Zhou

  • Asymptotically Exact A Posteriori Error Estimators, Part I: Grids with Superconvergence

    Randolph E. Bank;Jinchao Xu

  • ReLU Deep Neural Networks and Linear Finite Elements

    Juncai He;Lin Li;Jinchao Xu;Chunyue Zheng

  • The auxiliary space method and optimal multigrid preconditioning techniques for unstructured grids

    Jinchao Xu

  • Algebraic multigrid methods

    Jinchao Xu;Ludmil T. Zikatanov

  • Analysis of recovery type a posteriori error estimators for mildly structured grids

    Jinchao Xu;Zhimin Zhang

Frequent Co-Authors

James H. Bramble
James H. Bramble Texas A&M University
Michael Holst
Michael Holst University of California, San Diego
Joseph E. Pasciak
Joseph E. Pasciak Texas A&M University
Russell T. Johns
Russell T. Johns Pennsylvania State University
Randolph E. Bank
Randolph E. Bank University of California, San Diego
Ralf Hiptmair
Ralf Hiptmair ETH Zurich
Chao-Yang Wang
Chao-Yang Wang Pennsylvania State University
Ricardo H. Nochetto
Ricardo H. Nochetto University of Maryland, College Park
Tony F. Chan
Tony F. Chan University of California, Los Angeles
Panayot S. Vassilevski
Panayot S. Vassilevski Lawrence Livermore National Laboratory

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