World's Best Scientists 2026 revealed!
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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
96
Citations
34394
World Ranking
443
National Ranking
57

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2023 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award

Overview

Jie Tang is affiliated with Tsinghua University in China and has contributed extensively to the field of computer science. Their research spans several subfields, including artificial intelligence, computer vision and pattern recognition, molecular biology, materials chemistry, and information systems. Jie Tang's work is prominently focused on advanced computational techniques, particularly in machine learning and network analysis.

Key areas of research Jie Tang explores include:

  • Topic Modeling
  • Advanced Graph Neural Networks
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Complex Network Analysis Techniques
  • Recommender Systems and Techniques
  • Data Quality and Management

Jie Tang has authored a substantial number of publications, primarily in computer science. Notable recent papers illustrate a diverse interest in language models, graph-based methods, and generative AI technologies. These include:

  • Evaluating Large Language Models Trained on Code (2021), published in arXiv (Cornell University)
  • Pre-trained models: Past, present and future (2021), published in AI Open
  • Parameter-efficient fine-tuning of large-scale pre-trained language models (2023), published in Nature Machine Intelligence
  • GraphMAE: Self-Supervised Masked Graph Autoencoders (2022), published in Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • CogView: Mastering Text-to-Image Generation via Transformers (2021), published in arXiv (Cornell University)

Jie Tang's work appears regularly in multiple publication venues, reflecting consistent academic output across premier conferences and journals. Their frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • The Cambridge Structural Database
  • AI Open
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Collaboration has been an integral part of Jie Tang's research approach. They have worked frequently with several co-authors, including:

  • Yuxiao Dong
  • Ming Ding
  • Xiao Liu
  • Minlie Huang
  • Juanzi Li

This combination of extensive publication record, a broad range of topics, and active collaboration indicates Jie Tang's engagement in advancing computational methods and applications involving machine learning, natural language processing, and graph neural networks within computer science.

Best Publications

  • ArnetMiner: extraction and mining of academic social networks

    Jie Tang;Jing Zhang;Limin Yao;Juanzi Li

  • GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

    Jiezhong Qiu;Qibin Chen;Yuxiao Dong;Jing Zhang

  • Social influence analysis in large-scale networks

    Jie Tang;Jimeng Sun;Chi Wang;Zi Yang

  • Self-supervised Learning: Generative or Contrastive.

    Xiao Liu;Fanjin Zhang;Zhenyu Hou;Zhaoyu Wang

  • Pre-Trained Models: Past, Present and Future

    Xu Han;Zhengyan Zhang;Ning Ding;Yuxian Gu

  • Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

    Jiezhong Qiu;Yuxiao Dong;Hao Ma;Jian Li

  • Self-supervised Learning: Generative or Contrastive

    Xiao Liu;Fanjin Zhang;Zhenyu Hou;Li Mian

  • RiMOM: A Dynamic Multistrategy Ontology Alignment Framework

    Juanzi Li;Jie Tang;Yi Li;Qiong Luo

  • User-level sentiment analysis incorporating social networks

    Chenhao Tan;Lillian Lee;Jie Tang;Long Jiang

  • DeepInf: Social Influence Prediction with Deep Learning

    Jiezhong Qiu;Jian Tang;Hao Ma;Yuxiao Dong

  • Inferring social status and rich club effects in enterprise communication networks.

    Yuxiao Dong;Jie Tang;Nitesh V. Chawla;Tiancheng Lou

  • Representation Learning for Attributed Multiplex Heterogeneous Network

    Yukuo Cen;Xu Zou;Jianwei Zhang;Hongxia Yang

  • CogView: Mastering Text-to-Image Generation via Transformers

    Ming Ding;Zhuoyi Yang;Wenyi Hong;Wendi Zheng

  • Cross-domain collaboration recommendation

    Jie Tang;Sen Wu;Jimeng Sun;Hang Su

  • Inferring social ties across heterogenous networks

    Jie Tang;Tiancheng Lou;Jon Kleinberg

  • Understanding retweeting behaviors in social networks

    Zi Yang;Jingyi Guo;Keke Cai;Jie Tang

  • Mining topic-level influence in heterogeneous networks

    Lu Liu;Jie Tang;Jiawei Han;Meng Jiang

  • COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

    Yutao Zhang;Jie Tang;Zhilin Yang;Jian Pei

  • Expert Finding in a Social Network

    Jing Zhang;Jie Tang;Juanzi Li

  • Link Prediction and Recommendation across Heterogeneous Social Networks

    Yuxiao Dong;Jie Tang;Sen Wu;Jilei Tian

  • A Unified Probabilistic Framework for Name Disambiguation in Digital Library

    Jie Tang;Alvis C. M. Fong;Bo Wang;Jing Zhang

  • Graph Random Neural Networks for Semi-Supervised Learning on Graphs

    Wenzheng Feng;Jie Zhang;Yuxiao Dong;Yu Han

Frequent Co-Authors

Juanzi Li
Juanzi Li Tsinghua University
Ying Ding
Ying Ding The University of Texas at Austin
Yuxiao Dong
Yuxiao Dong Tsinghua University
Hanghang Tong
Hanghang Tong University of Illinois at Urbana-Champaign
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Jimeng Sun
Jimeng Sun University of Illinois at Urbana-Champaign
Nitesh V. Chawla
Nitesh V. Chawla University of Notre Dame
Zhong Su
Zhong Su Alibaba Group (China)
Kuansan Wang
Kuansan Wang Microsoft (United States)

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