Ding Lu
Impact in
- Computational Mathematics top 10%
- Numerical Analysis top 10%
- Advanced Optimization Algorithms Research
Papers in
-
- Matrix Theory and Algorithms 9
- Co-authors
- Zhaojun Bai (6 shared papers)Yangfeng Su (2 shared papers)Yijing Chen (1 shared paper)Ling Yuan (1 shared paper)Bart Vandereycken (4 shared papers)Xiaobin Zhang (1 shared paper)Rongmei Kong (1 shared paper)Daoshan Yang (1 shared paper)
- Journals
- SIAM Journal on Matrix Analysis and Applications (7 papers)Systems & Control Letters (1 paper)International Journal for Numerical Methods in Engineering (1 paper)ACS Omega (1 paper)IEEE Transactions on Geoscience and Remote Sensing (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Ding Lu
26 papers receiving 392 citations
Peers
Comparison fields: 5 of 84
- Computational Mathematics 9
- Numerical Analysis 35
- Computational Theory and Mathematics 50
- Spectroscopy 45
- Materials Chemistry 108
Countries citing papers authored by Ding Lu
This map shows the geographic impact of Ding Lu'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 Ding Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ding Lu more than expected).
Fields of papers citing papers by Ding Lu
This network shows the impact of papers produced by Ding Lu. 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 Ding Lu. The network helps show where Ding Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ding Lu, 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 | 2016 | 67 | |
| 2 | 2017 | 53 | |
| 3 | 2016 | 43 | |
| 4 | 2023 | 34 | |
| 5 | 2019 | 31 | |
| 6 | 2017 | 26 | |
| 7 | 2015 | 24 | |
| 8 | 2017 | 22 | |
| 9 | 2018 | 20 | |
| 10 | 2019 | 16 | |
| 11 | 2019 | 11 | |
| 12 | 2022 | 11 | |
| 13 | 2018 | 10 | |
| 14 | 2019 | 8 | |
| 15 | 2015 | 7 | |
| 16 | 2017 | 4 | |
| 17 | 2016 | 3 | |
| 18 | 2018 | 3 | |
| 19 | 2024 | 3 | |
| 20 | 2023 | 3 |
About Ding Lu
Ding Lu is a scholar working on Computational Theory and Mathematics, Numerical Analysis, Computational Mechanics, Computer Vision and Pattern Recognition and Signal Processing, having authored 28 papers that have together received 409 indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (9 papers), Sparse and Compressive Sensing Techniques (3 papers), Advanced biosensing and bioanalysis techniques (3 papers), Carbon and Quantum Dots Applications (2 papers), Model Reduction and Neural Networks (2 papers), Molecular Sensors and Ion Detection (2 papers), Electrochemical sensors and biosensors (2 papers) and Electromagnetic Scattering and Analysis (2 papers). The work is most often cited by research in Computational Mathematics (9 citations), Numerical Analysis (35 citations), Computational Theory and Mathematics (50 citations), Spectroscopy (45 citations) and Materials Chemistry (108 citations). Ding Lu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Zhaojun Bai, Yangfeng Su, Yijing Chen, Ling Yuan, Bart Vandereycken, Xiaobin Zhang, Rongmei Kong, Daoshan Yang, Fengli Qu and Gang Zhou. Their work appears in journals such as SIAM Journal on Matrix Analysis and Applications, Systems & Control Letters, International Journal for Numerical Methods in Engineering, ACS Omega and IEEE Transactions on Geoscience and Remote Sensing.
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.