Zhe Quan

1.3k total citations
44 papers, 780 citations indexed

About

Zhe Quan is a scholar working on Computer Networks and Communications, Artificial Intelligence and Hardware and Architecture. According to data from OpenAlex, Zhe Quan has authored 44 papers receiving a total of 780 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 13 papers in Artificial Intelligence and 12 papers in Hardware and Architecture. Recurrent topics in Zhe Quan's work include Parallel Computing and Optimization Techniques (11 papers), Topic Modeling (5 papers) and Cloud Computing and Resource Management (4 papers). Zhe Quan is often cited by papers focused on Parallel Computing and Optimization Techniques (11 papers), Topic Modeling (5 papers) and Cloud Computing and Resource Management (4 papers). Zhe Quan collaborates with scholars based in China, United States and France. Zhe Quan's co-authors include Xuan Lin, Xiangxiang Zeng, Zhijie Wang, Zhi-Jie Wang, Chu-Min Li, Tengfei Ma, Kenli Li, Huang Huang, Ting Ye and Song Guo and has published in prestigious journals such as Expert Systems with Applications, Sensors and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Zhe Quan

43 papers receiving 765 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhe Quan China 14 319 265 263 166 115 44 780
Huimin Zhang China 12 251 0.8× 101 0.4× 92 0.3× 98 0.6× 65 0.6× 60 533
Jun Huan United States 16 166 0.5× 165 0.6× 277 1.1× 70 0.4× 56 0.5× 53 694
Alexander Hall Switzerland 12 60 0.2× 70 0.3× 178 0.7× 397 2.4× 54 0.5× 27 860
Akihiro Inokuchi Japan 9 151 0.5× 141 0.5× 345 1.3× 81 0.5× 48 0.4× 27 705
K. V. Prema India 11 133 0.4× 117 0.4× 84 0.3× 122 0.7× 43 0.4× 55 521
Taneli Mielikäinen Finland 13 202 0.6× 210 0.8× 314 1.2× 171 1.0× 14 0.1× 21 832
Stefan Hougardy Germany 14 253 0.8× 55 0.2× 93 0.4× 171 1.0× 14 0.1× 43 680
Shuhong Gao United States 22 396 1.2× 138 0.5× 618 2.3× 95 0.6× 13 0.1× 87 1.3k
Wilfried N. Gansterer Austria 14 86 0.3× 45 0.2× 237 0.9× 390 2.3× 21 0.2× 64 830

Countries citing papers authored by Zhe Quan

Since Specialization
Citations

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

Fields of papers citing papers by Zhe Quan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhe Quan

This figure shows the co-authorship network connecting the top 25 collaborators of Zhe Quan. A scholar is included among the top collaborators of Zhe Quan 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 Zhe Quan. Zhe Quan 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.
Quan, Zhe & Jun Sun. (2025). A Feature-Enhanced Small Object Detection Algorithm Based on Attention Mechanism. Sensors. 25(2). 589–589. 1 indexed citations
2.
Quan, Zhe, et al.. (2025). NtNDet: Hardware Trojan detection based on pre-trained language models. Expert Systems with Applications. 271. 126666–126666. 1 indexed citations
3.
Quan, Zhe, et al.. (2024). $\boldsymbol{R}^{2}$: A Novel Recall & Ranking Framework for Legal Judgment Prediction. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 1609–1622. 3 indexed citations
4.
Cao, Da, et al.. (2024). Graph Reasoning With Supervised Contrastive Learning for Legal Judgment Prediction. IEEE Transactions on Neural Networks and Learning Systems. 36(2). 2801–2815. 2 indexed citations
5.
Graillat, Stef, et al.. (2023). XHYPRE: a reliable parallel numerical algorithm library for solving large-scale sparse linear equations. 5(2). 191–209. 1 indexed citations
6.
Barrio, Roberto, et al.. (2022). PACF: A precision-adjustable computational framework for solving singular values. Applied Mathematics and Computation. 440. 127611–127611. 1 indexed citations
7.
Wang, Zhi-Jie, et al.. (2022). Cover Trees Revisited: Exploiting Unused Distance and Direction Information. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11231–11245.
8.
Lin, Xuan, Zhe Quan, Zhi-Jie Wang, et al.. (2022). Effectively Identifying Compound-Protein Interaction Using Graph Neural Representation. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(2). 932–943. 10 indexed citations
9.
Lin, Xuan, Zhe Quan, Zhijie Wang, Tengfei Ma, & Xiangxiang Zeng. (2020). KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction. 2739–2745. 214 indexed citations
10.
Yin, Jian, et al.. (2020). A Novel Model for Imbalanced Data Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 6680–6687. 25 indexed citations
11.
Quan, Zhe, et al.. (2019). An Efficient Framework for Sentence Similarity Modeling. IEEE/ACM Transactions on Audio Speech and Language Processing. 27(4). 853–865. 46 indexed citations
12.
Quan, Zhe, Yan Guo, Xuan Lin, Zhijie Wang, & Xiangxiang Zeng. (2019). GraphCPI: Graph Neural Representation Learning for Compound-Protein Interaction. 717–722. 22 indexed citations
13.
Wang, Zhijie, et al.. (2019). An Improved Hierarchical Datastructure for Nearest Neighbor Search. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 10001–10002. 1 indexed citations
14.
Chen, Yuedan, et al.. (2018). Implementation and optimization of a data protecting model on the Sunway TaihuLight supercomputer with heterogeneous many‐core processors. Concurrency and Computation Practice and Experience. 31(21). 7 indexed citations
15.
Li, Kenli, et al.. (2018). Implementing molecular dynamics simulation on the Sunway TaihuLight system with heterogeneous many‐core processors. Concurrency and Computation Practice and Experience. 30(16). 12 indexed citations
16.
Quan, Zhe, et al.. (2018). An Efficient Method for Optimizing PETSc on the Sunway TaihuLight System. 51. 538–545. 2 indexed citations
17.
Ye, Ting, et al.. (2018). ISAECC: An Improved Scheduling Approach for Energy Consumption Constrained Parallel Applications on Heterogeneous Distributed Systems. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4. 267–274. 4 indexed citations
18.
Quan, Zhe, et al.. (2016). Implementing Molecular Dynamics Simulation on Sunway TaihuLight System. 443–450. 19 indexed citations
19.
Quan, Zhe & Lei Wu. (2016). Design and evaluation of a parallel neighbor algorithm for the disjunctively constrained knapsack problem. Concurrency and Computation Practice and Experience. 29(20). 7 indexed citations
20.
Li, Chu-Min & Zhe Quan. (2010). An Efficient Branch-and-Bound Algorithm Based on MaxSAT for the Maximum Clique Problem. Proceedings of the AAAI Conference on Artificial Intelligence. 24(1). 128–133. 66 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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