Jinjing Zhou

1.4k total citations
5 papers, 391 citations indexed

About

Jinjing Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Physiology. According to data from OpenAlex, Jinjing Zhou has authored 5 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Physiology. Recurrent topics in Jinjing Zhou's work include Advanced Graph Neural Networks (3 papers), Graph Theory and Algorithms (2 papers) and Topic Modeling (2 papers). Jinjing Zhou is often cited by papers focused on Advanced Graph Neural Networks (3 papers), Graph Theory and Algorithms (2 papers) and Topic Modeling (2 papers). Jinjing Zhou collaborates with scholars based in China, Hong Kong and United States. Jinjing Zhou's co-authors include Zheng Zhang, Minjie Wang, Chao Ma, Da Zheng, Jinyang Li, Yu Gai, Lingfan Yu, Qi Huang, Quan Gan and Haibin Lin and has published in prestigious journals such as BMC Psychiatry, arXiv (Cornell University) and PubMed.

In The Last Decade

Jinjing Zhou

4 papers receiving 383 citations

Peers

Jinjing Zhou

AI

CVPR

CNC

EEE

IS

Lingfan Yu China

Ziyue Huang China

Ke Yuan China

Zaixi Zhang China

Bettina Messmer Switzerland

Christoph Goller Germany

Qingqing Long China

Deyu Bo China

Tianle Cai China

Jonathan Frankle United States

Lingfan Yu China

Jinjing Zhou

188 ×0.7

AI

114 ×0.7

CVPR

62 ×1.0

CNC

57 ×1.2

EEE

40 ×0.9

IS

Citations per year, relative to Jinjing Zhou Jinjing Zhou (= 1×) peers Lingfan Yu

Countries citing papers authored by Jinjing Zhou

Since Specialization

Citations

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

Fields of papers citing papers by Jinjing Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinjing Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Jinjing Zhou. A scholar is included among the top collaborators of Jinjing Zhou 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 Jinjing Zhou. Jinjing Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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5 of 5 papers shown

1.

Shen, Hui, Jinjing Zhou, Yan Liu, et al.. (2024). Shen-based Qigong Exercise improves cognitive impairment in stable schizophrenia patients in rehabilitation wards: a randomized controlled study. BMC Psychiatry. 24(1). 796–796.

2.

Yan, Xiao, et al.. (2023). DGI: An Easy and Efficient Framework for GNN Model Evaluation. 5439–5450. 6 indexed citations

3.

Bai, Tingting, Haiyan Jin, Xin Sun, et al.. (2022). Cognitive impairment is associated with sarcopenia mainly related to attention and calculation in hospitalized Chinese elderly men.. PubMed. 31(3). 534–542. 5 indexed citations

4.

Zheng, Da, Chao Ma, Minjie Wang, et al.. (2020). DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. 36–44. 120 indexed citations

5.

Wang, Minjie, Lingfan Yu, Da Zheng, et al.. (2019). Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. arXiv (Cornell University). 260 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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