Shuiwang Ji

Active 2006–2026

248
Papers
19,071
Citations
66
h-index
175
i10-index

Citations

Citations per year for Shuiwang Ji1926: 1 citations1967: 1 citations1969: 1 citations1974: 2 citations1986: 1 citations1991: 1 citations1992: 1 citations1993: 1 citations1994: 1 citations1995: 1 citations1996: 1 citations1997: 3 citations2001: 1 citations2003: 2 citations2004: 1 citations2005: 1 citations2006: 9 citations2007: 2 citations2008: 13 citations2009: 64 citations2010: 158 citations2011: 168 citations2012: 247 citations2013: 310 citations2014: 380 citations2015: 378 citations2016: 455 citations2017: 579 citations2018: 609 citations2019: 752 citations2020: 753 citations2021: 1,056 citations2022: 1,095 citations2023: 1,171 citations2024: 1,552 citations2025: 1,487 citations2026: 452 citations2027: 1 citations1927–1966: no citations, so these years are not shown1968: no citations, so this year is not shown1970–1973: no citations, so these years are not shown1975–1985: no citations, so these years are not shown1987–1990: no citations, so these years are not shown1998–2000: no citations, so these years are not shown2002: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 4,432 citing papers, 35.4% of this breakdownUnited States: 2,615 citing papers, 20.9% of this breakdownAustralia: 543 citing papers, 4.3% of this breakdownUnited Kingdom: 505 citing papers, 4% of this breakdownHong Kong: 394 citing papers, 3.1% of this breakdownIndia: 360 citing papers, 2.9% of this breakdownCanada: 322 citing papers, 2.6% of this breakdownSouth Korea: 300 citing papers, 2.4% of this breakdownSingapore: 284 citing papers, 2.3% of this breakdownGermany: 277 citing papers, 2.2% of this breakdownFrance: 219 citing papers, 1.8% of this breakdownJapan: 183 citing papers, 1.5% of this breakdown
0%35.4%Other 16.6%

Fields

  • Computer Science60.9%
  • Engineering9.4%
  • Medicine6.9%
  • Biochemistry, Genetics and Molecular Biology6.5%
  • Neuroscience4.7%
  • Materials Science2.2%
  • Other9.4%

Topics

  • Advanced Graph Neural Networks6%
  • Face and Expression Recognition3.8%
  • Topic Modeling2.7%
  • Domain Adaptation and Few-Shot Learning2.4%
  • Sparse and Compressive Sensing Techniques2.3%
  • Text and Document Classification Technologies2.2%
  • Other80.6%

Coauthors

All papers

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  1. TrustLLM: Trustworthiness in Large Language Models

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao - arXiv (Cornell University), CoRR 2024 cited by 410

  2. Explainability in Graph Neural Networks: A Taxonomic Survey

    Authors: , , , - IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Trans. Pattern Anal. Mach. Intell. 2022 cited by 498

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

    Authors: , , , , - IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Trans. Pattern Anal. Mach. Intell. 2022 cited by 365

  4. Towards Deeper Graph Neural Networks

    Authors: , , - SIGKDD International Conference on Knowledge Discovery & Data Mining 2020 cited by 501

  5. XGNN: Towards Model-Level Explanations of Graph Neural Networks

    Authors: , , , - SIGKDD International Conference on Knowledge Discovery & Data Mining 2020 cited by 264

  6. Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru‐Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Žitnik, Anima Anandkumar, Stefano Ermon, Píetro Lió, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji - Foundations and Trends® in Machine Learning, Found. Trends Mach. Learn. 2025 cited by 141

  7. Graph U-Nets

    Authors: , - IEEE Transactions on Pattern Analysis and Machine Intelligence, ICML 2019 cited by 1,315

  8. Large-Scale Learnable Graph Convolutional Networks

    Authors: , , - SIGKDD International Conference on Knowledge Discovery & Data Mining 2018 cited by 458

  9. Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding

    Authors: , , , , , , , , , , - NeurIPS 2025 cited by 124

  10. Adversarial Attacks and Defenses on Graphs

    Authors: , , , , , , - ACM SIGKDD Explorations Newsletter, SIGKDD Explor. 2020 cited by 162

  11. Deep Adversarial Learning for Multi-Modality Missing Data Completion

    Authors: , , , , - SIGKDD International Conference on Knowledge Discovery & Data Mining 2018 cited by 160

  12. A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery

    Authors: , , , , , , - Conference on Empirical Methods in Natural Language Processing, EMNLP 2024 cited by 57

  13. Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning

    Authors: , , , , , , , , , , - arXiv (Cornell University), CoRR 2025 cited by 56

  14. Generating 3D Molecules for Target Protein Binding

    Authors: , , , , - ICML 2022 cited by 186

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

    Authors: , , , , , , - NeuroImage 2015 cited by 831

  16. Advanced graph and sequence neural networks for molecular property prediction and drug discovery

    Authors: , , , , , , , , , , - Bioinformatics, Bioinform. 2022 cited by 114

  17. Generative AI for Autonomous Driving: Frontiers and Opportunities

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Eun Hak Lee, Xuan Di, Xinyue Ye, Liu Ren, Alois Knoll, Xiaopeng Li, Shuiwang Ji, Masayoshi Tomizuka, Marco Pavone, Tianbao Yang, Jing Du, Ming–Hsuan Yang, Wei Hua, Ziran Wang, Yang Zhou, Jiachen Li, Zhengzhong Tu - ArXiv.org, CoRR 2025 cited by 44

  18. Feature Selection Based on Structured Sparsity: A Comprehensive Study

    Authors: , , , , - IEEE Transactions on Neural Networks and Learning Systems, IEEE Trans. Neural Networks Learn. Syst. 2016 cited by 339

  19. Political-LLM: Large Language Models in Political Science

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong - arXiv (Cornell University), CoRR 2024 cited by 39

  20. Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis

    Authors: , , , , , , - Lecture notes in computer science, MICCAI (3) 2014 cited by 486

  21. Spherical Message Passing for 3D Molecular Graphs

    Authors: , , , , , , - ICLR 2022 cited by 265

  22. Eliminating Position Bias of Language Models: A Mechanistic Approach

    Authors: , , , , , , , , - ICLR 2025 cited by 78

  23. On Explainability of Graph Neural Networks via Subgraph Explorations

    Authors: , , , , - ICML 2021 cited by 540

  24. Non-Local U-Nets for Biomedical Image Segmentation

    Authors: , , , - AAAI Conference on Artificial Intelligence 2020 cited by 188