Jin Qi

3.2k citations
112 papers · 2.5k indexed · 1 hit paper · h-index 23

Impact in

Papers in

Jin Qi

104 papers receiving 2.5k citations

Hit Papers

Ultrasmall Sn Nanoparticles Embedded in Nitrogen-Doped Porous Carbon As High-Performance Anode for Lithium-Ion Batteries 2013 · 538 citations
5382013202620172021100200300400500

Peers

Jin Qi
Comparison fields: 5 of 166
  • Management of Technology and Innovation 189
  • Management Science and Operations Research 296
  • Electronic, Optical and Magnetic Materials 371
  • Rehabilitation 134
  • Biomaterials 227
Replace Fangyi Li with:
Fangyi Li China
Ben Wang United States
Wen Feng Lu Singapore
Yinghong Peng China
Chenghai Li China
Jun Ni United States
Jörg Franke Germany
Gong Wang China
An Liu China
Namhun Kim South Korea
Jin Qi relative to Fangyi Li China Fangyi Li's profile →
Citations per field
00.5×5.6×
Fangyi Li · 1×
Citations per year

Countries citing papers authored by Jin Qi

Since Specialization
Citations

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

Fields of papers citing papers by Jin Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Jin Qi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jin Qi Line = papers co-authored together Jin Qi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
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3 20255
4 20256
5 20250
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11 20232
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13 202311
14 202312
15 2020127
16
Planetary Gearbox Fault Diagnosis Based on Multiple Feature Extraction and Information Fusion Combined with Deep Learning
20196
17 2018113
18 20154
19 20148
20 20109

About Jin Qi

Jin Qi is a scholar working on Management of Technology and Innovation, Industrial and Manufacturing Engineering, Management Science and Operations Research, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 112 papers that have together received 2.5k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (15 papers), Quality Function Deployment in Product Design (15 papers), Robot Manipulation and Learning (10 papers), Product Development and Customization (10 papers), Manufacturing Process and Optimization (9 papers), Neuroscience and Neural Engineering (8 papers), Color perception and design (8 papers) and EEG and Brain-Computer Interfaces (7 papers). The work is most often cited by research in Management of Technology and Innovation (189 citations), Management Science and Operations Research (296 citations), Electronic, Optical and Magnetic Materials (371 citations), Rehabilitation (134 citations) and Biomaterials (227 citations). Jin Qi has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jie Hu, Yinghong Peng, Zhiqiang Zhu, Jing Du, Shiwen Wang, Jun Chen, Tianran Zhang, Fangyi Cheng, Guo‐Niu Zhu and Wenguo Cui. Their work appears in journals such as Advanced Engineering Informatics, Applied Sciences, Expert Systems with Applications, Engineering Applications of Artificial Intelligence and Information Sciences.

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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