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D-Index & Metrics

Mathematics

D-Index
39
Citations
6059
World Ranking
2216
National Ranking
935

Engineering and Technology

D-Index
41
Citations
6552
World Ranking
6996
National Ranking
1909

Overview

Lili Ju is a researcher affiliated with the University of South Carolina in the United States. Their work spans multiple disciplines including engineering, computer science, and mathematics, with a strong focus on numerical analysis and computational mechanics.

The main areas of study in their research include:

  • Numerical Analysis
  • Computational Mechanics
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Materials Chemistry

Lili Ju has contributed extensively to topics related to differential equations and numerical methods, advanced numerical methods in computational mathematics, and numerical methods for differential equations. Additional research topics cover solidification and crystal growth phenomena, model reduction and neural networks, advanced mathematical modeling in engineering, and advanced graph neural networks.

Frequent publication venues for Lili Ju include:

  • arXiv (Cornell University)
  • Journal of Computational Physics
  • Journal of Scientific Computing
  • SSRN Electronic Journal
  • Computer Methods in Applied Mechanics and Engineering

Frequent co-authors collaborating with Lili Ju are:

  • Zhu Wang
  • Zhonghua Qiao
  • Rihui Lan
  • Anthony Gruber
  • Max Gunzburger

Recent publications by Lili Ju include:

  • Maximum Bound Principles for a Class of Semilinear Parabolic Equations and Exponential Time-Differencing Schemes, 2021, SIAM Review
  • Maximum bound principle preserving integrating factor Runge-Kutta methods for semilinear parabolic equations, 2021, Journal of Computational Physics
  • Stabilized Integrating Factor Runge--Kutta Method and Unconditional Preservation of Maximum Bound Principle, 2021, SIAM Journal on Scientific Computing
  • Generalized SAV-Exponential Integrator Schemes for Allen--Cahn Type Gradient Flows, 2022, SIAM Journal on Numerical Analysis
  • A comparison of neural network architectures for data-driven reduced-order modeling, 2022, Computer Methods in Applied Mechanics and Engineering

Best Publications

  • Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations

    Qiang Du;Maria Emelianenko;Lili Ju

  • Constrained Centroidal Voronoi Tessellations for Surfaces

    Qiang Du;Max D. Gunzburger;Lili Ju

  • Maximum principle preserving exponential time differencing schemes for the nonlocal Allen Cahn equation

    Qiang Du;Lili Ju;Xiao Li;Xiao Li;Xiao Li;Zhonghua Qiao

  • Probabilistic methods for centroidal Voronoi tessellations and their parallel implementations

    Lili Ju;Qiang Du;Max Gunzburger

  • Maximum bound principles for a class of semilinear parabolic equations and exponential time-differencing schemes

    Qiang Du;Lili Ju;Xiao Li;Xiao Li;Zhonghua Qiao

  • P-MVSNet: Learning Patch-Wise Matching Confidence Aggregation for Multi-View Stereo

    Keyang Luo;Tao Guan;Lili Ju;Haipeng Huang

  • Efficient linear schemes with unconditional energy stability for the phase field elastic bending energy model

    Xiaofeng Yang;Xiaofeng Yang;Lili Ju

  • A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations

    Todd Ringler;Lili Ju;Max Gunzburger

  • DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation

    Xinyi Wu;Zhenyao Wu;Hao Guo;Lili Ju

  • Linear and unconditionally energy stable schemes for the binary fluid–surfactant phase field model

    Xiaofeng Yang;Lili Ju

  • Fast Explicit Integration Factor Methods for Semilinear Parabolic Equations

    Lili Ju;Jian Zhang;Liyong Zhu;Qiang Du

  • Semantic Stereo Matching With Pyramid Cost Volumes

    Zhenyao Wu;Xinyi Wu;Xiaoping Zhang;Song Wang

  • Exploring a Multiresolution Modeling Approach within the Shallow-Water Equations

    Todd D. Ringler;Doug Jacobsen;Max Gunzburger;Lili Ju

  • Energy stability and error estimates of exponential time differencing schemes for the epitaxial growth model without slope selection

    Lili Ju;Xiao Li;Zhonghua Qiao;Hui Zhang

  • Stabilized linear semi-implicit schemes for the nonlocal Cahn–Hilliard equation

    Qiang Du;Lili Ju;Xiao Li;Zhonghua Qiao

  • Voronoi-based finite volume methods, optimal Voronoi meshes, and PDEs on the sphere ☆

    Qiang Du;Max D. Gunzburger;Lili Ju

  • An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation

    Jie Wang;Lili Ju;Xiaoqiang Wang

  • Attention-Aware Multi-View Stereo

    Keyang Luo;Tao Guan;Lili Ju;Yuesong Wang

  • A Stable Multistep Scheme for Solving Backward Stochastic Differential Equations

    Weidong Zhao;Guannan Zhang;Lili Ju

  • Voronoi Tessellations and Their Application to Climate and Global Modeling

    Lili Ju;Todd Ringler;Max Gunzburger

  • Meshfree, probabilistic determination of point sets and support regions for meshless computing

    Qiang Du;Max Gunzburger;Lili Ju

  • Advances in Studies and Applications of Centroidal Voronoi Tessellations

    Qiang Du;Max Gunzburger;Lili Ju

Frequent Co-Authors

Max D. Gunzburger
Max D. Gunzburger Florida State University
Qiang Du
Qiang Du Columbia University
Xiao Li
Xiao Li China University of Mining and Technology
Song Wang
Song Wang University of South Carolina
Stephen F. Price
Stephen F. Price Los Alamos National Laboratory
Roger Temam
Roger Temam Indiana University
Yu Cao
Yu Cao University of Minnesota
Li-Shi Luo
Li-Shi Luo Old Dominion University
Gaël Durand
Gaël Durand Grenoble Alpes University
Xiao-Ping Zhang
Xiao-Ping Zhang University of Birmingham

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