World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
28576
World Ranking
2824
National Ranking
1396

Research.com Recognitions

  • 2020 - ACM Distinguished Member
  • 2018 - ACM Senior Member

Overview

Shuiwang Ji is affiliated with Texas A&M University in the United States and specializes in computer science, with a primary focus on artificial intelligence and its applications. Their research encompasses a variety of interdisciplinary subfields including materials chemistry, computer vision and pattern recognition, molecular biology, and biophysics.

The scientist's work spans multiple topics prominently featuring advanced graph neural networks, machine learning in materials science, topic modeling, computational drug discovery methods, explainable artificial intelligence (XAI), domain adaptation and few-shot learning, and protein structure and dynamics.

Frequent collaborators of Shuiwang Ji include:

  • Yaochen Xie
  • Youzhi Luo
  • Zhengyang Wang
  • Shurui Gui
  • Meng Liu

Shuiwang Ji has contributed extensively to academic literature, publishing in several notable venues. The most frequent publication venues are:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Nature Methods
  • IEEE Transactions on Medical Imaging

Examples of recent papers include:

  • Explainability in Graph Neural Networks: A Taxonomic Survey, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Self-Supervised Learning of Graph Neural Networks: A Unified Review, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Line Graph Neural Networks for Link Prediction, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Graph U-Nets, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Non-Local U-Nets for Biomedical Image Segmentation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Shuiwang Ji has been recognized by the Association for Computing Machinery (ACM) with distinctions including:

  • ACM Distinguished Member, 2020
  • ACM Senior Member, 2018

The research profile of Shuiwang Ji reflects a blend of computational techniques applied to both theoretical and applied problems, particularly within machine learning and its intersection with scientific domains such as materials science and molecular biology.

Best Publications

  • 3D Convolutional Neural Networks for Human Action Recognition

    Shuiwang Ji;Wei Xu;Ming Yang;Kai Yu

  • Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.

    Wenlu Zhang;Rongjian Li;Houtao Deng;Li Wang

  • Multi-task feature learning via efficient l 2, 1 -norm minimization

    Jun Liu;Shuiwang Ji;Jieping Ye

  • Large-Scale Learnable Graph Convolutional Networks

    Hongyang Gao;Zhengyang Wang;Shuiwang Ji

  • Graph U-Nets.

    Hongyang Gao;Shuiwang Ji

  • Deep learning based imaging data completion for improved brain disease diagnosis.

    Rongjian Li;Wenlu Zhang;Heung Il Suk;Li Wang

  • An accelerated gradient method for trace norm minimization

    Shuiwang Ji;Jieping Ye

  • SLEP: Sparse Learning with Efficient Projections

    Jun Liu;Shuiwang Ji;Jieping Ye

  • Explainability in Graph Neural Networks: A Taxonomic Survey.

    Hao Yuan;Haiyang Yu;Shurui Gui;Shuiwang Ji

  • Towards Deeper Graph Neural Networks

    Meng Liu;Hongyang Gao;Shuiwang Ji

  • Partial Least Squares

    Liang Sun;Shuiwang Ji;Jieping Ye

  • XGNN: Towards Model-Level Explanations of Graph Neural Networks

    Hao Yuan;Jiliang Tang;Xia Hu;Shuiwang Ji

  • Feature Selection Based on Structured Sparsity: A Comprehensive Study

    Jie Gui;Zhenan Sun;Shuiwang Ji;Dacheng Tao

  • Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis

    Liang Sun;Shuiwang Ji;Jieping Ye

  • Self-Supervised Learning of Graph Neural Networks: A Unified Review

    Yaochen Xie;Zhao Xu;Zhengyang Wang;Shuiwang Ji

  • A Robust Deep Model for Improved Classification of AD/MCI Patients

    Feng Li;Loc Tran;Kim-Han Thung;Shuiwang Ji

  • Discriminant sparse neighborhood preserving embedding for face recognition

    Jie Gui;Zhenan Sun;Wei Jia;Rongxiang Hu

  • Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

    Wenlu Zhang;Rongjian Li;Tao Zeng;Qian Sun

  • Hypergraph spectral learning for multi-label classification

    Liang Sun;Shuiwang Ji;Jieping Ye

  • Extracting shared subspace for multi-label classification

    Shuiwang Ji;Lei Tang;Shipeng Yu;Jieping Ye

  • Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning

    Ting Kei Pong;Paul Tseng;Shuiwang Ji;Jieping Ye

  • Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization

    Jun Liu;Shuiwang Ji;Jieping Ye

Frequent Co-Authors

Jieping Ye
Jieping Ye Alibaba Group (China)
Sudhir Kumar
Sudhir Kumar Temple University
Xia Hu
Xia Hu Rice University
Dinggang Shen
Dinggang Shen ShanghaiTech University
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Jiang Li
Jiang Li Shanghai Jiao Tong University
Ian Davidson
Ian Davidson University of California, Davis
Jun Liu
Jun Liu Infinia ML (United States)
Yao Zhao
Yao Zhao Beijing Jiaotong University
Zhenan Sun
Zhenan Sun Chinese Academy of Sciences

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