Junliang Yu

4.0k total citations · 5 hit papers
49 papers, 2.3k citations indexed

About

Junliang Yu is a scholar working on Information Systems, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Junliang Yu has authored 49 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Information Systems, 24 papers in Artificial Intelligence and 15 papers in Electrical and Electronic Engineering. Recurrent topics in Junliang Yu's work include Recommender Systems and Techniques (30 papers), Advanced Graph Neural Networks (18 papers) and Fuel Cells and Related Materials (13 papers). Junliang Yu is often cited by papers focused on Recommender Systems and Techniques (30 papers), Advanced Graph Neural Networks (18 papers) and Fuel Cells and Related Materials (13 papers). Junliang Yu collaborates with scholars based in China, Australia and Germany. Junliang Yu's co-authors include Hongzhi Yin, Xin Xia, Lizhen Cui, Quoc Viet Hung Nguyen, Xiangliang Zhang, Qinyong Wang, Jundong Li, Tong Chen, Min Gao and Zi Huang and has published in prestigious journals such as Journal of Power Sources, International Journal of Hydrogen Energy and IEEE Access.

In The Last Decade

Junliang Yu

43 papers receiving 2.3k citations

Hit Papers

Self-Supervised Hypergraph Convolutional Networks for Ses... 2021 2026 2022 2024 2021 2022 2021 2023 2023 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
    2021 339 citations Hongzhi Yin, Junliang Yu et al. profile →
  2. Are Graph Augmentations Necessary?
    2022 298 citations Junliang Yu, Hongzhi Yin et al. profile →
  3. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation
    2021 294 citations Junliang Yu, Hongzhi Yin et al. profile →
  4. Self-Supervised Learning for Recommender Systems: A Survey
    2023 197 citations Junliang Yu, Hongzhi Yin et al. IEEE Transactions on Knowledge and Data Engineering profile →
  5. XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
    2023 154 citations Junliang Yu, Tong Chen et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junliang Yu China 19 1.7k 1.6k 407 260 249 49 2.3k
Guibing Guo China 26 2.1k 1.2× 1.4k 0.9× 577 1.4× 468 1.8× 374 1.5× 91 2.5k
Wenwu Ou China 16 1.6k 1.0× 1.3k 0.8× 546 1.3× 184 0.7× 454 1.8× 30 2.1k
Xu Chen China 20 1.3k 0.8× 1.3k 0.8× 487 1.2× 228 0.9× 330 1.3× 121 2.1k
Peng Jiang China 18 1.5k 0.9× 1.2k 0.8× 476 1.2× 135 0.5× 472 1.9× 58 2.0k
Xiaolin Gui China 20 693 0.4× 1.1k 0.7× 220 0.5× 608 2.3× 102 0.4× 143 1.9k
Yue Shi Netherlands 19 1.5k 0.9× 882 0.5× 570 1.4× 264 1.0× 398 1.6× 45 2.0k
Changhua Pei China 10 1.2k 0.7× 988 0.6× 380 0.9× 223 0.9× 339 1.4× 30 1.6k
Jian-Tao Sun China 24 1.0k 0.6× 1.8k 1.1× 409 1.0× 136 0.5× 102 0.4× 56 2.6k
Binbin Hu China 14 1.1k 0.7× 1.7k 1.0× 280 0.7× 265 1.0× 112 0.4× 46 2.1k

Countries citing papers authored by Junliang Yu

Since Specialization
Citations

This map shows the geographic impact of Junliang Yu'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 Junliang Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junliang Yu more than expected).

Fields of papers citing papers by Junliang Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Junliang Yu. 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 Junliang Yu. The network helps show where Junliang Yu may publish in the future.

Co-authorship network of co-authors of Junliang Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Junliang Yu. A scholar is included among the top collaborators of Junliang Yu 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 Junliang Yu. Junliang Yu 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.
2.
Yu, Junliang, et al.. (2025). BiasNavi: LLM-Empowered Data Bias Management. 2939–2942.
3.
4.
Yu, Junliang, et al.. (2025). Graph Condensation: A Survey. IEEE Transactions on Knowledge and Data Engineering. 37(4). 1819–1837. 8 indexed citations
5.
6.
Chen, Tong, et al.. (2025). Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition. 4359–4373. 3 indexed citations
7.
Qu, Liang, et al.. (2025). Harnessing Large Language Models for Group POI Recommendations. 1968–1978.
8.
Zhang, Wentao, et al.. (2024). Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation. 3042–3055. 7 indexed citations
9.
Guo, Lei, et al.. (2024). Motif-based Prompt Learning for Universal Cross-domain Recommendation. 257–265. 8 indexed citations
10.
Yu, Junliang, et al.. (2024). Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks. 3311–3322. 4 indexed citations
11.
Gao, Min, et al.. (2023). Efficient Bi-Level Optimization for Recommendation Denoising. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2502–2511. 19 indexed citations
12.
Xia, Xin, Junliang Yu, Guandong Xu, & Hongzhi Yin. (2023). Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation. 2795–2804. 6 indexed citations
13.
Yu, Junliang, Hongzhi Yin, Xin Xia, et al.. (2023). Self-Supervised Learning for Recommender Systems: A Survey. IEEE Transactions on Knowledge and Data Engineering. 36(1). 335–355. 197 indexed citations breakdown →
14.
Gao, Chongming, et al.. (2022). Who are the Best Adopters? User Selection Model for Free Trial Item Promotion. IEEE Transactions on Big Data. 9(2). 746–757. 7 indexed citations
15.
Wang, Qinyong, Hongzhi Yin, Tong Chen, et al.. (2021). Fast-adapting and privacy-preserving federated recommender system. The VLDB Journal. 31(5). 877–896. 78 indexed citations
16.
Yu, Junliang, Hongzhi Yin, Jundong Li, et al.. (2020). Enhancing Social Recommendation With Adversarial Graph Convolutional Networks. IEEE Transactions on Knowledge and Data Engineering. 34(8). 3727–3739. 122 indexed citations
17.
Yu, Junliang, Dieter Froning, Uwe Reimer, & Werner Lehnert. (2019). Polytetrafluorethylene effects on liquid water flowing through the gas diffusion layer of polymer electrolyte membrane fuel cells. Journal of Power Sources. 438. 226975–226975. 31 indexed citations
18.
Froning, Dieter, Junliang Yu, Uwe Reimer, & Werner Lehnert. (2018). Stochastic Analysis of the Gas Flow at the Gas Diffusion Layer/Electrode Interface of a High-Temperature Polymer Electrolyte Fuel Cell. Transport in Porous Media. 123(2). 403–420. 5 indexed citations
19.
Froning, Dieter, Junliang Yu, Uwe Reimer, & Werner Lehnert. (2018). Stochastic Analysis of the Gas Flow at the Gas Diffusion Layer/Channel Interface of a High-Temperature Polymer Electrolyte Fuel Cell. Applied Sciences. 8(12). 2536–2536. 4 indexed citations
20.
Froning, Dieter, Junliang Yu, Gerd Gaiselmann, et al.. (2016). Impact of compression on gas transport in non-woven gas diffusion layers of high temperature polymer electrolyte fuel cells. Journal of Power Sources. 318. 26–34. 39 indexed citations

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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