2026 Jie Tang: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	96	443	431	57	55	489	34394

Jie Tang publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Jie Tang sits on this spectrum.

32 publications 991+

This scientist: 489 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Jie Tang D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Jie Tang sits on this spectrum.

30 D-Index 131+

This scientist: 96 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

2539
Citations
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Jiezhong Qiu;Qibin Chen;Yuxiao Dong;Jing Zhang

1273
Citations
Social influence analysis in large-scale networks

Jie Tang;Jimeng Sun;Chi Wang;Zi Yang

1212
Citations
Self-supervised Learning: Generative or Contrastive.

Xiao Liu;Fanjin Zhang;Zhenyu Hou;Zhaoyu Wang

1055
Citations
Pre-Trained Models: Past, Present and Future

Xu Han;Zhengyan Zhang;Ning Ding;Yuxian Gu

926
Citations
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

Jiezhong Qiu;Yuxiao Dong;Hao Ma;Jian Li

893
Citations
Self-supervised Learning: Generative or Contrastive

Xiao Liu;Fanjin Zhang;Zhenyu Hou;Li Mian

700
Citations
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework

Juanzi Li;Jie Tang;Yi Li;Qiong Luo

584
Citations
User-level sentiment analysis incorporating social networks

Chenhao Tan;Lillian Lee;Jie Tang;Long Jiang

553
Citations
DeepInf: Social Influence Prediction with Deep Learning

Jiezhong Qiu;Jian Tang;Hao Ma;Yuxiao Dong

509
Citations
Inferring social status and rich club effects in enterprise communication networks.

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

439
Citations
Representation Learning for Attributed Multiplex Heterogeneous Network

Yukuo Cen;Xu Zou;Jianwei Zhang;Hongxia Yang

424
Citations
CogView: Mastering Text-to-Image Generation via Transformers

Ming Ding;Zhuoyi Yang;Wenyi Hong;Wendi Zheng

388
Citations
Cross-domain collaboration recommendation

Jie Tang;Sen Wu;Jimeng Sun;Hang Su

370
Citations
Inferring social ties across heterogenous networks

Jie Tang;Tiancheng Lou;Jon Kleinberg

361
Citations
Understanding retweeting behaviors in social networks

Zi Yang;Jingyi Guo;Keke Cai;Jie Tang

359
Citations
Mining topic-level influence in heterogeneous networks

Lu Liu;Jie Tang;Jiawei Han;Meng Jiang

354
Citations
COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

Yutao Zhang;Jie Tang;Zhilin Yang;Jian Pei

336
Citations
Expert Finding in a Social Network

Jing Zhang;Jie Tang;Juanzi Li

333
Citations
Link Prediction and Recommendation across Heterogeneous Social Networks

Yuxiao Dong;Jie Tang;Sen Wu;Jilei Tian

330
Citations
A Unified Probabilistic Framework for Name Disambiguation in Digital Library

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

299
Citations
Graph Random Neural Networks for Semi-Supervised Learning on Graphs

Wenzheng Feng;Jie Zhang;Yuxiao Dong;Yu Han

189
Citations

Frequent Co-Authors

Juanzi Li Tsinghua University

Ying Ding The University of Texas at Austin

Yuxiao Dong Tsinghua University

Marie-Francine Moens KU Leuven

Hanghang Tong University of Illinois at Urbana-Champaign

Jiawei Han University of Illinois at Urbana-Champaign

Jimeng Sun University of Illinois at Urbana-Champaign

Nitesh V. Chawla University of Notre Dame

Zhong Su Alibaba Group (China)

Kuansan Wang Microsoft (United States)

External Links

Wikipedia of Jie Tang Personal website of Jie Tang Google Scholar page

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