Chenchen Jing

711 total citations
35 papers, 480 citations indexed

About

Chenchen Jing is a scholar working on Mechanical Engineering, Automotive Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chenchen Jing has authored 35 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Mechanical Engineering, 11 papers in Automotive Engineering and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chenchen Jing's work include Additive Manufacturing Materials and Processes (15 papers), Additive Manufacturing and 3D Printing Technologies (11 papers) and Multimodal Machine Learning Applications (9 papers). Chenchen Jing is often cited by papers focused on Additive Manufacturing Materials and Processes (15 papers), Additive Manufacturing and 3D Printing Technologies (11 papers) and Multimodal Machine Learning Applications (9 papers). Chenchen Jing collaborates with scholars based in China, Australia and Canada. Chenchen Jing's co-authors include Yunde Jia, Changmeng Liu, Jiping Lu, Yuwei Wu, Qi Wu, Tianqiu Xu, Mingtao Pei, Shuyuan Ma, Hongli Fan and Xiaoxun Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Construction and Building Materials.

In The Last Decade

Chenchen Jing

31 papers receiving 469 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chenchen Jing China 14 239 162 133 121 35 35 480
Zhixin Yu China 11 132 0.6× 78 0.5× 162 1.2× 15 0.1× 19 0.5× 40 374
Guoming Huang China 11 108 0.5× 95 0.6× 194 1.5× 19 0.2× 12 0.3× 30 427
Hussein Alahmer Jordan 16 183 0.8× 26 0.2× 68 0.5× 92 0.8× 63 1.8× 21 512
Emre İsa Albak Türkiye 10 274 1.1× 11 0.1× 93 0.7× 50 0.4× 36 1.0× 27 420
Zhijun Li China 8 53 0.2× 69 0.4× 38 0.3× 31 0.3× 38 1.1× 20 374
Mindaugas Žilys Lithuania 11 84 0.4× 46 0.3× 27 0.2× 23 0.2× 15 0.4× 45 332
Fengchen Wang United States 10 116 0.5× 26 0.2× 137 1.0× 10 0.1× 8 0.2× 36 318
Peng Jin China 9 248 1.0× 11 0.1× 109 0.8× 31 0.3× 29 0.8× 28 439
Manzar Masud Pakistan 8 78 0.3× 58 0.4× 23 0.2× 117 1.0× 11 0.3× 23 347
Yibo Ai China 8 134 0.6× 69 0.4× 14 0.1× 14 0.1× 57 1.6× 29 281

Countries citing papers authored by Chenchen Jing

Since Specialization
Citations

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

Fields of papers citing papers by Chenchen Jing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chenchen Jing

This figure shows the co-authorship network connecting the top 25 collaborators of Chenchen Jing. A scholar is included among the top collaborators of Chenchen Jing 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 Chenchen Jing. Chenchen Jing 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.
Pang, Guansong, Chenchen Jing, Yuling Xi, et al.. (2025). CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning. IEEE Transactions on Neural Networks and Learning Systems. 36(8). 15137–15151. 1 indexed citations
3.
Liu, Changmeng, Jiawei Xie, Rui Fu, et al.. (2025). Effects of arc waveforms on morphology, microstructure, and properties of unsupported bars in wire and arc additive manufacturing. Journal of Materials Processing Technology. 337. 118722–118722. 4 indexed citations
4.
Jing, Chenchen, Tianqiu Xu, Yueling Guo, et al.. (2024). Impact of process parameters on forming quality and deposition efficiency of unsupported rods in wire arc additive manufacturing. Journal of Manufacturing Processes. 124. 12–23. 17 indexed citations
5.
Fu, Rui, et al.. (2024). Heat input adjustment process for unsupported aluminum alloy lattice struts continuous forming by wire arc-directed energy deposition. Journal of Materials Processing Technology. 332. 118550–118550. 4 indexed citations
6.
Jing, Chenchen, et al.. (2024). In-Context Compositional Generalization for Large Vision-Language Models. 17954–17966.
7.
Guo, Yueling, et al.. (2024). Enhanced high-temperature strength and ductility of wire arc additive manufactured Al–Ce–Mg alloys with fine α-Al/Al11Ce3 eutectics. Journal of Materials Research and Technology. 30. 4929–4938. 4 indexed citations
8.
Xu, Tianqiu, et al.. (2024). Parallel multi arc directed energy deposition: New way to achieve efficient manufacturing of large-size lattice sandwich structure. Additive manufacturing. 90. 104322–104322. 5 indexed citations
9.
Jing, Chenchen, Yukun Li, Hao Chen, & Chunhua Shen. (2024). Retrieval-Augmented Primitive Representations for Compositional Zero-Shot Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(3). 2652–2660. 4 indexed citations
10.
Jing, Chenchen, et al.. (2023). Improve the manufacturing efficiency of steel bars by using hot-wire pulse arc additive manufacturing. Journal of Manufacturing Processes. 89. 430–443. 16 indexed citations
11.
Liu, Changmeng, Tianqiu Xu, Kun Li, et al.. (2023). Quasi-static compressive behaviors of large-size titanium lattice sandwich structure based on pulse hot-wire arc additive manufacturing. Materials Science and Engineering A. 868. 144787–144787. 11 indexed citations
12.
Li, Zhen, et al.. (2023). Exploring the Effect of Primitives for Compositional Generalization in Vision-and-Language. 19092–19101. 4 indexed citations
13.
Jing, Chenchen, Tianqiu Xu, Qianru Wu, et al.. (2023). Fabricating 316 L stainless steel unsupported rods by controlling the flow of molten pool via wire arc additive manufacturing. Journal of Materials Processing Technology. 319. 118066–118066. 13 indexed citations
14.
Jing, Chenchen, et al.. (2023). Experimental study on mechanical properties and bond behavior of wire and arc additive manufacturing steel bar. Construction and Building Materials. 400. 132836–132836. 2 indexed citations
15.
Liu, Lingqiao, Chenchen Jing, Hao Chen, et al.. (2023). Learning Conditional Attributes for Compositional Zero-Shot Learning. 11197–11206. 29 indexed citations
16.
Jing, Chenchen, et al.. (2022). Learning the Dynamics of Visual Relational Reasoning via Reinforced Path Routing. Proceedings of the AAAI Conference on Artificial Intelligence. 36(1). 1122–1130. 3 indexed citations
17.
Jing, Chenchen, Yuwei Wu, Mingtao Pei, et al.. (2020). Visual-Semantic Graph Matching for Visual Grounding. 4041–4050. 26 indexed citations
18.
Mei, Xiang, Junhui Li, Chenchen Jing, et al.. (2019). Separation and recovery of phenols from an aqueous solution by a green membrane system. Journal of Cleaner Production. 251. 119675–119675. 36 indexed citations
19.
Jiang, Wei, et al.. (2019). Unsupervised deep quantization for object instance search. Neurocomputing. 362. 60–71. 3 indexed citations
20.
Wu, Qianru, et al.. (2017). Simulation of assembling cargo-hold spaceship pallets. IOP Conference Series Earth and Environmental Science. 69. 12129–12129.

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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