Rui Zhang

12.0k total citations · 3 hit papers
357 papers, 6.0k citations indexed

About

Rui Zhang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Rui Zhang has authored 357 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 139 papers in Artificial Intelligence, 110 papers in Computer Vision and Pattern Recognition and 84 papers in Signal Processing. Recurrent topics in Rui Zhang's work include Data Management and Algorithms (66 papers), Topic Modeling (46 papers) and Recommender Systems and Techniques (44 papers). Rui Zhang is often cited by papers focused on Data Management and Algorithms (66 papers), Topic Modeling (46 papers) and Recommender Systems and Techniques (44 papers). Rui Zhang collaborates with scholars based in China, Australia and United States. Rui Zhang's co-authors include Jianzhong Qi, Beng Chin Ooi, Yu Cui, H. V. Jagadish, Kian‐Lee Tan, Bayu Distiawan Trisedya, Lars Kulik, Kotagiri Ramamohanarao, Jin Huang and Xing Xie and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nano Letters.

In The Last Decade

Rui Zhang

313 papers receiving 5.8k citations

Hit Papers

Spider: A Large-Scale Human-Labe... 2005 2026 2012 2019 2018 2005 2025 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Rui Zhang China 38 2.5k 1.6k 1.3k 1.2k 1.1k 357 6.0k
Reynold Cheng Hong Kong 40 2.2k 0.9× 2.5k 1.6× 892 0.7× 1.2k 1.1× 2.1k 1.9× 185 5.9k
Kai Zheng China 46 2.2k 0.9× 1.6k 1.0× 968 0.7× 1.8k 1.6× 1.8k 1.6× 357 7.0k
Yannis Manolopoulos Greece 41 2.8k 1.1× 3.4k 2.2× 1.3k 1.0× 2.2k 1.9× 2.3k 2.0× 301 7.9k
Lina Yao Australia 46 3.0k 1.2× 688 0.4× 2.0k 1.5× 2.3k 2.0× 1.3k 1.1× 309 7.8k
Vincent W. Zheng Singapore 31 2.7k 1.1× 661 0.4× 1.1k 0.8× 1.3k 1.1× 667 0.6× 79 5.1k
Bin Cui China 44 3.9k 1.6× 1.1k 0.7× 2.0k 1.5× 3.0k 2.6× 1.9k 1.6× 368 7.8k
Guodong Long Australia 32 3.3k 1.3× 946 0.6× 1.1k 0.8× 744 0.6× 492 0.4× 136 6.8k
Qin Lv United States 36 1.2k 0.5× 679 0.4× 1.0k 0.8× 936 0.8× 1.5k 1.3× 144 5.3k
Bin Guo China 41 1.8k 0.7× 630 0.4× 1.2k 0.9× 1.1k 1.0× 1.5k 1.3× 437 7.5k
Sung‐Bae Cho South Korea 36 2.4k 1.0× 832 0.5× 1.8k 1.4× 486 0.4× 1.1k 0.9× 320 5.4k

Countries citing papers authored by Rui Zhang

Since Specialization
Citations

This map shows the geographic impact of Rui Zhang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rui Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rui Zhang more than expected).

Fields of papers citing papers by Rui Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rui Zhang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rui Zhang. The network helps show where Rui Zhang may publish in the future.

Co-authorship network of co-authors of Rui Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Rui Zhang. A scholar is included among the top collaborators of Rui Zhang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rui Zhang. Rui Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ren, Pengfei, Rui Zhang, Yunfeng Wang, et al.. (2025). Systematic benchmarking of high-throughput subcellular spatial transcriptomics platforms across human tumors. Nature Communications. 16(1). 9232–9232. 1 indexed citations
2.
Fan, Gilbert, et al.. (2025). The impact of AI-assisted pair programming on student motivation, programming anxiety, collaborative learning, and programming performance: a comparative study with traditional pair programming and individual approaches. International Journal of STEM Education. 12(1). 15 indexed citations breakdown →
3.
Khan, Naveed Ullah, Wasim Akram, Zaheer Khan, et al.. (2024). α-Lactalbumin based scaffolds for infected wound healing and tissue regeneration. International Journal of Pharmaceutics. 663. 124578–124578. 6 indexed citations
4.
Zhu, Jieming, Yanting Yang, Quanyu Dai, et al.. (2024). Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. 6566–6576. 13 indexed citations
5.
Zhao, Xiaoyan, Yang Deng, Min Yang, et al.. (2024). A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers. ACM Computing Surveys. 56(11). 1–39. 42 indexed citations
6.
Li, Yangning, Hai-Tao Zheng, Yinghui Li, et al.. (2024). MESED: A Multi-Modal Entity Set Expansion Dataset with Fine-Grained Semantic Classes and Hard Negative Entities. Proceedings of the AAAI Conference on Artificial Intelligence. 38(8). 8697–8706. 1 indexed citations
7.
Zhang, Rui, et al.. (2024). Exposure to Multiple Metal(loid)s and Hypertension in Chinese Older Adults. Biological Trace Element Research. 203(6). 2944–2959. 2 indexed citations
8.
Du, Zhaocheng, Jieming Zhu, D. Zou, et al.. (2024). UniEmbedding: Learning Universal Multi-Modal Multi-Domain Item Embeddings via User-View Contrastive Learning. 4446–4453. 1 indexed citations
9.
Lin, Jianghao, Weiwen Liu, Ruiming Tang, et al.. (2023). An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. 1057–1065. 9 indexed citations
10.
Li, Shiwei, Huifeng Guo, Lu Hou, et al.. (2023). Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4435–4443. 8 indexed citations
11.
Liu, Weiwen, Yang Wang, Ruiming Tang, et al.. (2023). On-device Integrated Re-ranking with Heterogeneous Behavior Modeling. 5225–5236. 3 indexed citations
12.
Zhang, Rui, Weiwei Xia, Feng Yan, & Lianfeng Shen. (2019). A single-site positioning method based on TOA and DOA estimation using virtual stations in NLOS environment. China Communications. 16(2). 146–159. 24 indexed citations
13.
Zhang, Rui, Cícero Nogueira dos Santos, Michihiro Yasunaga, Bing Xiang, & Dragomir Radev. (2018). Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering. 102–107. 42 indexed citations
14.
Wang, Xiaojie, Rui Zhang, Yu Sun, & Jianzhong Qi. (2018). KDGAN: Knowledge Distillation with Generative Adversarial Networks. Neural Information Processing Systems. 31. 775–786. 74 indexed citations
15.
Yao, Enjian, et al.. (2017). A Location Model of EV Public Charging Station Considering Drivers’ Daily Activities and Range Anxiety: Case Study of Beijing. Transportation Research Board 96th Annual MeetingTransportation Research Board. 2 indexed citations
16.
Bird, Steven, et al.. (2011). A Breadth-First Representation for Tree Matching in Large Scale Forest-Based Translation. International Joint Conference on Natural Language Processing. 785–793. 1 indexed citations
17.
Ramamohanarao, Kotagiri, et al.. (2011). Accelerating spatial join operations using bit-indices. Australasian Database Conference. 115. 123–132. 2 indexed citations
18.
Jiang, Jian, et al.. (2010). A real time hybrid pattern matching scheme for stock time series. Australasian Database Conference. 104. 161–170. 27 indexed citations
19.
Yang, Xiaokang, Rui Zhang, Yi Xu, et al.. (2008). Shanghai Jiao Tong University participation in high-level feature extraction, automatic search and surveillance event detectionat TRECVID 2008.. TRECVID. 1 indexed citations
20.
Kellar, Melanie, et al.. (2003). Dynamic Composition of Math Lessons. Educational Technology & Society. 6. 100–111.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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