Junhao Wen

5.0k total citations · 2 hit papers
184 papers, 3.4k citations indexed

About

Junhao Wen is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Junhao Wen has authored 184 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Information Systems, 70 papers in Artificial Intelligence and 54 papers in Computer Networks and Communications. Recurrent topics in Junhao Wen's work include Recommender Systems and Techniques (82 papers), Advanced Graph Neural Networks (29 papers) and Caching and Content Delivery (29 papers). Junhao Wen is often cited by papers focused on Recommender Systems and Techniques (82 papers), Advanced Graph Neural Networks (29 papers) and Caching and Content Delivery (29 papers). Junhao Wen collaborates with scholars based in China, Australia and United States. Junhao Wen's co-authors include Muhammad Mateen, Song Sun, Wei Zhou, Nasrullah Nasrullah, Min Gao, Quanwang Wu, Jun Zeng, Fengji Luo, Qingyu Xiong and Xiuhua Li and has published in prestigious journals such as PLoS ONE, Chemical Engineering Journal and Physical Chemistry Chemical Physics.

In The Last Decade

Junhao Wen

166 papers receiving 3.3k citations

Hit Papers

Fundus Image Classification Using VGG-19 Architecture wit... 2018 2026 2020 2023 2018 2022 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junhao Wen China 29 1.3k 1.1k 906 583 437 184 3.4k
Saurabh Singh South Korea 29 1.6k 1.2× 1.3k 1.2× 1.6k 1.8× 994 1.7× 542 1.2× 74 4.8k
V. Vijayakumar India 35 1.1k 0.8× 1000 0.9× 1.0k 1.1× 682 1.2× 721 1.6× 172 3.9k
Milan Tuba Serbia 36 435 0.3× 1.8k 1.7× 874 1.0× 850 1.5× 677 1.5× 160 3.7k
Hari Mohan Pandey United Kingdom 31 230 0.2× 923 0.9× 583 0.6× 909 1.6× 484 1.1× 113 3.1k
Shigen Shen China 38 842 0.6× 1.3k 1.2× 2.0k 2.2× 323 0.6× 676 1.5× 144 3.9k
Kuruva Lakshmanna India 23 335 0.3× 876 0.8× 646 0.7× 420 0.7× 387 0.9× 51 2.7k
Yuehui Chen China 33 296 0.2× 1.5k 1.4× 629 0.7× 403 0.7× 523 1.2× 250 3.8k
Zhiguang Qin China 34 1.1k 0.8× 1.8k 1.7× 1.1k 1.2× 1.2k 2.1× 679 1.6× 283 4.0k
Xiaochun Cheng United Kingdom 34 969 0.7× 1.5k 1.4× 1.4k 1.5× 535 0.9× 608 1.4× 219 3.9k
Abdu Gumaei Saudi Arabia 33 742 0.6× 1.4k 1.4× 1.3k 1.5× 705 1.2× 356 0.8× 133 4.2k

Countries citing papers authored by Junhao Wen

Since Specialization
Citations

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

Fields of papers citing papers by Junhao Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junhao Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Junhao Wen. A scholar is included among the top collaborators of Junhao Wen 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 Junhao Wen. Junhao Wen 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
2.
Yao, Liqiang, et al.. (2025). Localization and mapping method for forestry mobile platforms based on enhanced Hector SLAM. Journal of King Saud University - Computer and Information Sciences. 37(8).
3.
Yan, Tianci, Huamin Hu, Junfei Duan, et al.. (2024). Achieving superior sodium storage performance of sulfide heterostructures via copper-driven and electrochemical reconstruction strategy. Chemical Engineering Journal. 499. 155871–155871. 8 indexed citations
4.
Zhong, Lin, et al.. (2024). SCFL: Spatio-temporal consistency federated learning for next POI recommendation. Information Processing & Management. 61(6). 103852–103852. 9 indexed citations
5.
Zeng, Jun, et al.. (2024). CBRec: A causal way balancing multidimensional attraction effect in POI recommendations. Knowledge-Based Systems. 305. 112607–112607. 1 indexed citations
6.
Wang, Hongyu, et al.. (2024). Multiple hypergraph convolutional network social recommendation using dual contrastive learning. Data Mining and Knowledge Discovery. 38(4). 1929–1957. 3 indexed citations
7.
Zeng, Jun, et al.. (2024). Explainable next POI recommendation based on spatial–temporal disentanglement representation and pseudo profile generation. Knowledge-Based Systems. 309. 112784–112784. 2 indexed citations
8.
Yu, Yang, et al.. (2023). Multi-views contrastive learning for dense text retrieval. Knowledge-Based Systems. 274. 110624–110624. 1 indexed citations
9.
Zeng, Jun, et al.. (2023). Point-of-interest Recommendation using Deep Semantic Model. Expert Systems with Applications. 231. 120727–120727. 12 indexed citations
10.
Zhou, Wei, et al.. (2023). IHG4MR: Interest-oriented heterogeneous graph for multirelational recommendation. Expert Systems with Applications. 228. 120321–120321. 5 indexed citations
11.
Tang, Y.Y., Zhaoyong Chen, Feng Lin, et al.. (2023). Synergistic role of Sb doping and surface modification in high performance ultrahigh-nickel layered oxides cathode materials. Journal of Alloys and Compounds. 959. 170552–170552. 20 indexed citations
12.
Zeng, Jun, et al.. (2023). LGSA: A next POI prediction method by using local and global interest with spatiotemporal awareness. Expert Systems with Applications. 227. 120291–120291. 6 indexed citations
13.
Zhou, Wei, et al.. (2023). Noise-reducing graph neural network with intent-target co-action for session-based recommendation. Information Processing & Management. 60(6). 103517–103517. 10 indexed citations
14.
Yan, Tianci, Wen Fang, Junfei Duan, et al.. (2023). Fabricating tunable metal sulfides embedded with honeycomb-structured N-doped carbon matrices for high-performance lithium-ion capacitors. Chemical Engineering Journal. 474. 145839–145839. 28 indexed citations
15.
Wen, Junhao, et al.. (2022). Multi-interaction fusion collaborative filtering for social recommendation. Expert Systems with Applications. 205. 117610–117610. 10 indexed citations
16.
Fan, Qilin, Xiuhua Li, Jian Li, et al.. (2021). PA-Cache: Evolving Learning-Based Popularity- Aware Content Caching in Edge Networks. IEEE Transactions on Network and Service Management. 18(2). 1746–1757. 38 indexed citations
17.
Sun, Chuan, Xiongwei Wu, Xiuhua Li, et al.. (2021). Cooperative Computation Offloading for Multi-Access Edge Computing in 6G Mobile Networks via Soft Actor Critic. IEEE Transactions on Network Science and Engineering. 11(6). 5601–5614. 76 indexed citations
18.
Sun, Chuan, Hui Li, Xiuhua Li, et al.. (2020). Task Offloading for End-Edge-Cloud Orchestrated Computing in Mobile Networks. 1–6. 28 indexed citations
19.
Yang, Xiaofan, et al.. (2017). On the Optimal Dynamic Control Strategy of Disruptive Computer Virus. Discrete Dynamics in Nature and Society. 2017. 1–14. 20 indexed citations
20.
Xiong, Qingyu, et al.. (2014). Services Recommendation System based on Heterogeneous Network Analysis in Cloud Computing. Research Journal of Applied Sciences Engineering and Technology. 7(14). 2858–2862. 1 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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