Chaofan Ma

656 total citations
11 papers, 501 citations indexed

About

Chaofan Ma is a scholar working on Soil Science, Computer Vision and Pattern Recognition and Pollution. According to data from OpenAlex, Chaofan Ma has authored 11 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Soil Science, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Pollution. Recurrent topics in Chaofan Ma's work include Composting and Vermicomposting Techniques (5 papers), Pharmaceutical and Antibiotic Environmental Impacts (3 papers) and Visual Attention and Saliency Detection (2 papers). Chaofan Ma is often cited by papers focused on Composting and Vermicomposting Techniques (5 papers), Pharmaceutical and Antibiotic Environmental Impacts (3 papers) and Visual Attention and Saliency Detection (2 papers). Chaofan Ma collaborates with scholars based in China, Malaysia and Australia. Chaofan Ma's co-authors include Qiuhui Zhu, Qunliang Li, Xintian Li, Zhiwei Jiang, Mingqi Li, Gen Li, Jiaqi Xu, Youyan Liu, Siew Yoong Leong and Qingyun Li and has published in prestigious journals such as Journal of Hazardous Materials, Bioresource Technology and Fuel.

In The Last Decade

Chaofan Ma

11 papers receiving 500 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chaofan Ma China 10 244 145 91 90 90 11 501
Tianbao Ren China 15 199 0.8× 87 0.6× 51 0.6× 159 1.8× 88 1.0× 38 583
Xiqing Wang China 16 103 0.4× 166 1.1× 197 2.2× 141 1.6× 168 1.9× 46 768
M. Kalbasi Iran 13 248 1.0× 136 0.9× 105 1.2× 242 2.7× 17 0.2× 35 584
Shi-Peng Wang China 14 635 2.6× 359 2.5× 289 3.2× 124 1.4× 80 0.9× 22 878
Nanyi Wang China 12 223 0.9× 190 1.3× 100 1.1× 80 0.9× 38 0.4× 20 458
Shengtao Xu China 16 228 0.9× 55 0.4× 46 0.5× 377 4.2× 107 1.2× 33 741
Ghulām Qādir Pakistan 14 89 0.4× 49 0.3× 58 0.6× 206 2.3× 350 3.9× 53 724
Siobhán N. Jordan Ireland 11 77 0.3× 95 0.7× 138 1.5× 76 0.8× 44 0.5× 20 385
Huilin Feng China 10 139 0.6× 62 0.4× 23 0.3× 100 1.1× 40 0.4× 20 368
Seishu Tojo Japan 11 42 0.2× 30 0.2× 50 0.5× 197 2.2× 84 0.9× 38 427

Countries citing papers authored by Chaofan Ma

Since Specialization
Citations

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

Fields of papers citing papers by Chaofan Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chaofan Ma

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

All Works

11 of 11 papers shown
1.
Ma, Chaofan, et al.. (2025). DARF: Depth-Aware Generalizable Neural Radiance Field. Displays. 88. 102996–102996. 1 indexed citations
2.
Wang, Yu, et al.. (2024). Annotation-free Audio-Visual Segmentation. 5592–5602. 12 indexed citations
3.
Yan, Hailong, Qiuqi Niu, Qiuhui Zhu, et al.. (2021). Biochar reinforced the populations of cbbL-containing autotrophic microbes and humic substance formation via sequestrating CO2 in composting process. Journal of Biotechnology. 333. 39–48. 39 indexed citations
4.
5.
Ma, Chaofan, Xiangfeng Wang, Bo Jin, et al.. (2020). Boundary-Aware Supervoxel-Level Iteratively Refined Interactive 3D Image Segmentation With Multi-Agent Reinforcement Learning. IEEE Transactions on Medical Imaging. 40(10). 2563–2574. 14 indexed citations
6.
7.
Li, Gen, Qiuhui Zhu, Zhiwei Jiang, et al.. (2020). Roles of non-ionic surfactant sucrose ester on the conversion of organic matters and bacterial community structure during composting. Bioresource Technology. 308. 123279–123279. 22 indexed citations
8.
Zhu, Qiuhui, Gen Li, Zhiwei Jiang, et al.. (2020). Investigating the variation of dissolved organic matters and the evolution of autotrophic microbial community in composting with organic and inorganic carbon sources. Bioresource Technology. 304. 123013–123013. 50 indexed citations
9.
Jiang, Zhiwei, Xintian Li, Mingqi Li, et al.. (2020). Impacts of red mud on lignin depolymerization and humic substance formation mediated by laccase-producing bacterial community during composting. Journal of Hazardous Materials. 410. 124557–124557. 109 indexed citations
10.
Yang, Jiachen, Yinghao Zhu, Chaofan Ma, Wen Lu, & Qinggang Meng. (2018). Stereoscopic video quality assessment based on 3D convolutional neural networks. Neurocomputing. 309. 83–93. 25 indexed citations
11.
Zhang, Yu‐Qing, et al.. (2009). Modification of cellulase and its application to extraction of diosgenin from Dioscorea zingiberensis C.H. Wright. Biochemical Engineering Journal. 47(1-3). 80–86. 37 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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