Lingjun Liu
Impact in
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- Electric Power System Optimization
- Smart Grid Energy Management
- Integrated Energy Systems Optimization
Papers in
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- Photoacoustic and Ultrasonic Imaging 8
- Nanoplatforms for cancer theranostics 4
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- Image and Signal Denoising Methods 9
- Co-authors
- Benxi Liu (4 shared papers)Shengli Liao (4 shared papers)Xiaoyu Jin (4 shared papers)Chuntian Cheng (3 shared papers)Jay R. Lund (3 shared papers)Hong Liu (5 shared papers)Deju Ye (4 shared papers)Ruibing An (3 shared papers)
- Journals
- IEEE Access (3 papers)Signal Processing (2 papers)Energy Conversion and Management (1 paper)Knowledge-Based Systems (1 paper)Science Advances (1 paper)
- Partner nations
- ChinaUnited StatesCzechia
In The Last Decade
Lingjun Liu
32 papers receiving 643 citations
Peers
Comparison fields: 5 of 101
- Energy Engineering and Power Technology 41
- Electrical and Electronic Engineering 225
- Biomedical Engineering 165
- Water Science and Technology 48
- Biomaterials 44
Countries citing papers authored by Lingjun Liu
This map shows the geographic impact of Lingjun Liu'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 Lingjun Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingjun Liu more than expected).
Fields of papers citing papers by Lingjun Liu
This network shows the impact of papers produced by Lingjun Liu. 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 Lingjun Liu. The network helps show where Lingjun Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Lingjun Liu, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 166 | |
| 2 | 2022 | 95 | |
| 3 | 2023 | 69 | |
| 4 | 2022 | 47 | |
| 5 | 2021 | 37 | |
| 6 | 2024 | 31 | |
| 7 | 2018 | 29 | |
| 8 | 2020 | 22 | |
| 9 | 2021 | 21 | |
| 10 | 2020 | 20 | |
| 11 | 2020 | 19 | |
| 12 | 2023 | 14 | |
| 13 | 2020 | 13 | |
| 14 | 2022 | 13 | |
| 15 | 2024 | 9 | |
| 16 | 2019 | 5 | |
| 17 | 2021 | 5 | |
| 18 | 2017 | 5 | |
| 19 | 2022 | 4 | |
| 20 | 2020 | 4 |
About Lingjun Liu
Lingjun Liu is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition, Computational Mechanics, Electrical and Electronic Engineering and Ocean Engineering, having authored 36 papers that have together received 650 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (10 papers), Image and Signal Denoising Methods (9 papers), Photoacoustic and Ultrasonic Imaging (8 papers), Electric Power System Optimization (4 papers), Nanoplatforms for cancer theranostics (4 papers), Catalytic C–H Functionalization Methods (3 papers), Luminescence and Fluorescent Materials (3 papers) and Advanced Image Fusion Techniques (3 papers). The work is most often cited by research in Energy Engineering and Power Technology (41 citations), Electrical and Electronic Engineering (225 citations), Biomedical Engineering (165 citations), Water Science and Technology (48 citations) and Biomaterials (44 citations). Lingjun Liu has collaborated with scholars based in China, United States and Czechia. Frequent co-authors include Benxi Liu, Shengli Liao, Xiaoyu Jin, Chuntian Cheng, Jay R. Lund, Hong Liu, Deju Ye, Ruibing An, Zheng Huang and Kaixian Chen. Their work appears in journals such as IEEE Access, Signal Processing, Energy Conversion and Management, Knowledge-Based Systems and Science Advances.
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.