Cuicui Ji
Impact in
- Neurology top 10%
- Neurological diseases and metabolism
-
- Remote Sensing and LiDAR Applications
Papers in
- Ecology 11
- Remote Sensing in Agriculture 9
-
- Remote Sensing and LiDAR Applications 8
- Co-authors
- Yan Zhao (4 shared papers)Hongyu Zhao (4 shared papers)Huayu Sun (3 shared papers)Xiaosong Li (8 shared papers)Xiaoqun Wang (2 shared papers)Guangyan Miao (2 shared papers)Noboru Mizushima (1 shared paper)Saori R. Yoshii (1 shared paper)
- Journals
- Autophagy (3 papers)Remote Sensing (3 papers)Current Biology (1 paper)Ecological Indicators (1 paper)Nature Communications (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Cuicui Ji
24 papers receiving 362 citations
Peers
Comparison fields: 5 of 77
- Neurology 75
- Environmental Engineering 66
- Epidemiology 145
- Ecology 96
- Cell Biology 58
Countries citing papers authored by Cuicui Ji
This map shows the geographic impact of Cuicui Ji'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 Cuicui Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cuicui Ji more than expected).
Fields of papers citing papers by Cuicui Ji
This network shows the impact of papers produced by Cuicui Ji. 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 Cuicui Ji. The network helps show where Cuicui Ji may publish in the future.
Co-authors
The 25 scholars most cited alongside Cuicui Ji, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 111 | |
| 2 | 2021 | 43 | |
| 3 | 2019 | 40 | |
| 4 | 2016 | 35 | |
| 5 | 2020 | 30 | |
| 6 | 2016 | 22 | |
| 7 | 1996 | 22 | |
| 8 | 2023 | 10 | |
| 9 | 2018 | 10 | |
| 10 | 2017 | 8 | |
| 11 | 2024 | 8 | |
| 12 | 2016 | 4 | |
| 13 | 2025 | 3 | |
| 14 | 2024 | 3 | |
| 15 | 2024 | 3 | |
| 16 | 2024 | 3 | |
| 17 | 2021 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2022 | 2 |
About Cuicui Ji
Cuicui Ji is a scholar working on Ecology, Environmental Engineering, Media Technology, Global and Planetary Change and Molecular Biology, having authored 28 papers that have together received 368 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (9 papers), Remote Sensing and LiDAR Applications (8 papers), Remote-Sensing Image Classification (5 papers), Endoplasmic Reticulum Stress and Disease (4 papers), 3D Surveying and Cultural Heritage (4 papers), Remote Sensing and Land Use (4 papers), Soil erosion and sediment transport (3 papers) and Advanced Image Fusion Techniques (3 papers). The work is most often cited by research in Neurology (75 citations), Environmental Engineering (66 citations), Epidemiology (145 citations), Ecology (96 citations) and Cell Biology (58 citations). Cuicui Ji has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yan Zhao, Hongyu Zhao, Huayu Sun, Xiaosong Li, Xiaoqun Wang, Guangyan Miao, Noboru Mizushima, Saori R. Yoshii, Le Sun and Hong Zhang. Their work appears in journals such as Autophagy, Remote Sensing, Current Biology, Ecological Indicators and Nature Communications.
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.