M. Zuhair Nashed
- Computational Theory and Mathematics top 0.5%
- Applied Mathematics top 0.5%
- Mathematical Physics top 1%
- Numerical Analysis top 1%
- Computer Vision and Pattern Recognition top 2%
- Co-authors
- Hans SaganW. J. KammererWilli FreedenFengshan LiuXiaojun ChenThomas SonarGrace WahbaQiyu Sun
- Topics
- Numerical methods in inverse problems (31 papers)Matrix Theory and Algorithms (29 papers)Mathematical Analysis and Transform Methods (17 papers)
- Journals
- Mathematics of ComputationSIAM Journal on Numerical AnalysisJournal of Mathematical Analysis and Applications
- Partner nations
- United StatesGermanyMalaysia
In The Last Decade
M. Zuhair Nashed
97 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 118
- Computational Theory and Mathematics 813
- Applied Mathematics 714
- Mathematical Physics 605
- Numerical Analysis 452
- Computer Vision and Pattern Recognition 371
Countries citing papers authored by M. Zuhair Nashed
This map shows the geographic impact of M. Zuhair Nashed'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 M. Zuhair Nashed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Zuhair Nashed more than expected).
Fields of papers citing papers by M. Zuhair Nashed
This network shows the impact of papers produced by M. Zuhair Nashed. 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 M. Zuhair Nashed. The network helps show where M. Zuhair Nashed may publish in the future.
Co-authorship network of co-authors of M. Zuhair Nashed
This figure shows the co-authorship network connecting the top 25 collaborators of M. Zuhair Nashed. A scholar is included among the top collaborators of M. Zuhair Nashed 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 M. Zuhair Nashed. M. Zuhair Nashed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 61 | |
| 4 | 8 | |
| 5 | Inverse problems, image analysis, and medical imaging : AMS Special Session on Interaction of Inverse Problems and Image Analysis, January 10-13, 2001, New Orleans, Louisiana | 2 |
| 6 | 46 | |
| 7 | 1 | |
| 8 | 42 | |
| 9 | 9 | |
| 10 | 3 | |
| 11 | Algebraic and topological selections of multi-valued linear relations | 3 |
| 12 | 84 | |
| 13 | 6 | |
| 14 | 27 | |
| 15 | 15 | |
| 16 | 6 | |
| 17 | 39 | |
| 18 | 22 | |
| 19 | 47 | |
| 20 | 6 |
About M. Zuhair Nashed
M. Zuhair Nashed is a scholar working on Mathematical Physics, Applied Mathematics and Numerical Analysis, having authored 104 papers that have together received 2.2k indexed citations. Recurring topics across this work include Numerical methods in inverse problems (31 papers), Matrix Theory and Algorithms (29 papers) and Mathematical Analysis and Transform Methods (17 papers). The work is most often cited by research in Numerical Analysis (452 citations), Applied Mathematics (714 citations) and Mathematical Physics (605 citations). M. Zuhair Nashed has collaborated with scholars based in United States, Germany and Malaysia. Frequent co-authors include Hans Sagan, W. J. Kammerer, Willi Freeden, Fengshan Liu, Xiaojun Chen, Thomas Sonar, Grace Wahba, Qiyu Sun, Gilbert G. Walter and Otmar Scherzer. Their work appears in journals such as Mathematics of Computation, SIAM Journal on Numerical Analysis and Journal of Mathematical Analysis and Applications.
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.