World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
6569
World Ranking
9756
National Ranking
4116

Overview

Meng Jiang is affiliated with the University of Notre Dame in the United States. Their research primarily spans the field of Computer Science with a specific concentration in Artificial Intelligence, which accounts for most of their publications. Other subfields of study include Information Systems, Computer Vision and Pattern Recognition, Materials Chemistry, and Computer Networks and Communications.

Their work covers several main topics, including Topic Modeling, Advanced Graph Neural Networks, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Complex Network Analysis Techniques, Machine Learning in Materials Science, and Sentiment Analysis and Opinion Mining.

Recent papers authored by Meng Jiang include:

  • Data Augmentation for Graph Neural Networks, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • A Survey of Knowledge-enhanced Text Generation, 2022, ACM Computing Surveys
  • Few-Shot Knowledge Graph Completion, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Graph Few-Shot Learning via Knowledge Transfer, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • A Survey on Data-driven Network Intrusion Detection, 2021, ACM Computing Surveys

Frequent co-authors who have collaborated with Meng Jiang include:

  • Nitesh V. Chawla (17 publications together)
  • Tong Zhao (13 publications together)
  • Wenhao Yu (13 publications together)
  • Chenguang Zhu (13 publications together)
  • Shuohang Wang (8 publications together)

Key venues where Meng Jiang's work has been frequently published encompass:

  • arXiv (Cornell University) with 36 publications
  • Proceedings of the AAAI Conference on Artificial Intelligence with 5 publications
  • IEEE Transactions on Knowledge and Data Engineering with 3 publications
  • ACM Computing Surveys with 2 publications
  • ACM Transactions on Intelligent Systems and Technology with 2 publications

Meng Jiang has contributed to book publications with reputable publishers, including Springer Nature and the American Chemical Society. Titles include Knowledge-augmented Methods for Natural Language Processing (2024) and Modeling Polymers with Neural Networks (2025).

Best Publications

  • Social contextual recommendation

    Meng Jiang;Peng Cui;Rui Liu;Qiang Yang

  • Mining topic-level influence in heterogeneous networks

    Lu Liu;Jie Tang;Jiawei Han;Meng Jiang

  • Automated Phrase Mining from Massive Text Corpora

    Jingbo Shang;Jialu Liu;Meng Jiang;Xiang Ren

  • Data Augmentation for Graph Neural Networks

    Tong Zhao;Yozen Liu;Leonardo Neves;Oliver J. Woodford

  • Data Augmentation for Graph Neural Networks

    Tong Zhao;Yozen Liu;Leonardo Neves;Oliver Woodford

  • A Survey of Knowledge-Enhanced Text Generation.

    Wenhao Yu;Chenguang Zhu;Zaitang Li;Zhiting Hu

  • Scalable Recommendation with Social Contextual Information

    Meng Jiang;Peng Cui;Fei Wang;Wenwu Zhu

  • CatchSync: catching synchronized behavior in large directed graphs

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • Few-Shot Knowledge Graph Completion

    Chuxu Zhang;Huaxiu Yao;Chao Huang;Meng Jiang

  • Artificial intelligence based smart energy community management: A reinforcement learning approach

    Suyang Zhou;Zijian Hu;Wei Gu;Meng Jiang

  • Graph Few-shot Learning via Knowledge Transfer

    Huaxiu Yao;Chuxu Zhang;Ying Wei;Meng Jiang

  • A Survey on Data-driven Network Intrusion Detection

    Unknown

  • Suspicious Behavior Detection: Current Trends and Future Directions

    Meng Jiang;Peng Cui;Christos Faloutsos

  • Social Recommendation with Cross-Domain Transferable Knowledge

    Meng Jiang;Peng Cui;Xumin Chen;Fei Wang

  • Few-Shot Graph Learning for Molecular Property Prediction

    Zhichun Guo;Chuxu Zhang;Wenhao Yu;John Herr

  • Few-Shot Graph Learning for Molecular Property Prediction

    Zhichun Guo;Chuxu Zhang;Wenhao Yu;John Herr

  • Combined heat and power system intelligent economic dispatch : a deep reinforcement learning approach

    Suyang Zhou;Zijian Hu;Wei Gu;Meng Jiang

  • Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT Models

    Jinfeng Lin;Yalin Liu;Qingkai Zeng;Meng Jiang

  • Enhancing Factual Consistency of Abstractive Summarization

    Chenguang Zhu;William Hinthorn;Ruochen Xu;Qingkai Zeng

  • Inferring Strange Behavior from Connectivity Pattern in Social Networks

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • Social recommendation across multiple relational domains

    Meng Jiang;Peng Cui;Fei Wang;Qiang Yang

  • A General Suspiciousness Metric for Dense Blocks in Multimodal Data

    Meng Jiang;Alex Beutel;Peng Cui;Bryan Hooi

  • Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering

    Chao Zhang;Fangbo Tao;Xiusi Chen;Jiaming Shen

  • Large-Scale Embedding Learning in Heterogeneous Event Data

    Huan Gui;Jialu Liu;Fangbo Tao;Meng Jiang

Frequent Co-Authors

Nitesh V. Chawla
Nitesh V. Chawla University of Notre Dame
Shiqiang Yang
Shiqiang Yang Tsinghua University
Peng Cui
Peng Cui Tsinghua University
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Bing Qin
Bing Qin Harbin Institute of Technology
Ting Liu
Ting Liu Harbin Institute of Technology
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Xiang Ren
Xiang Ren University of Southern California
Yiyu Shi
Yiyu Shi University of Notre Dame
Wenwu Zhu
Wenwu Zhu Tsinghua University

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