J. Morais
Impact in
- Applied Mathematics top 1%
- Mathematical Analysis and Transform Methods
- Algebraic and Geometric Analysis
- Holomorphic and Operator Theory
- Signal Processing top 5%
- Digital Filter Design and Implementation
Papers in
-
- Algebraic and Geometric Analysis 51
- Mathematical Analysis and Transform Methods 28
- Holomorphic and Operator Theory 20
-
- Mathematics and Applications 15
- Analytic and geometric function theory 10
- Co-authors
- Kit Ian Kou (14 shared papers)Klaus Gürlebeck (14 shared papers)Svetlin G. Georgiev (6 shared papers)Wolfgang Sprößig (3 shared papers)M. Abul‐Ez (3 shared papers)Hanaa M. Zayed (4 shared papers)Mohra Zayed (3 shared papers)Mingsheng Liu (3 shared papers)
In The Last Decade
J. Morais
59 papers receiving 588 citations
Peers
Comparison fields: 5 of 49
- Applied Mathematics 532
- Signal Processing 139
- Geometry and Topology 111
- Algebra and Number Theory 38
- Computer Vision and Pattern Recognition 153
Countries citing papers authored by J. Morais
This map shows the geographic impact of J. Morais'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 J. Morais with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Morais more than expected).
Fields of papers citing papers by J. Morais
This network shows the impact of papers produced by J. Morais. 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 J. Morais. The network helps show where J. Morais may publish in the future.
Co-authors
The 25 scholars most cited alongside J. Morais, 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 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 79 | |
| 2 | 2014 | 66 | |
| 3 | 2014 | 54 | |
| 4 | 2012 | 49 | |
| 5 | 2016 | 38 | |
| 6 | 2011 | 23 | |
| 7 | 2018 | 19 | |
| 8 | 2016 | 17 | |
| 9 | 2012 | 17 | |
| 10 | 2021 | 15 | |
| 11 | 2013 | 14 | |
| 12 | 2009 | 12 | |
| 13 | 2012 | 12 | |
| 14 | 2011 | 12 | |
| 15 | 2012 | 11 | |
| 16 | 2007 | 10 | |
| 17 | 2014 | 9 | |
| 18 | 2014 | 9 | |
| 19 | 2021 | 8 | |
| 20 | 2014 | 7 |
About J. Morais
J. Morais is a scholar working on Applied Mathematics, Geometry and Topology, Algebra and Number Theory, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 597 indexed citations. Recurring topics across this work include Algebraic and Geometric Analysis (51 papers), Mathematical Analysis and Transform Methods (28 papers), Holomorphic and Operator Theory (20 papers), Mathematics and Applications (15 papers), Analytic and geometric function theory (10 papers), Advanced Topics in Algebra (8 papers), Matrix Theory and Algorithms (7 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Applied Mathematics (532 citations), Signal Processing (139 citations), Geometry and Topology (111 citations), Algebra and Number Theory (38 citations) and Computer Vision and Pattern Recognition (153 citations). J. Morais has collaborated with scholars based in Portugal, Germany and Mexico. Frequent co-authors include Kit Ian Kou, Klaus Gürlebeck, Svetlin G. Georgiev, Wolfgang Sprößig, M. Abul‐Ez, Hanaa M. Zayed, Mohra Zayed, Mingsheng Liu, M. Ferreira and Mohamed Abdalla. Their work appears in journals such as Mathematical Methods in the Applied Sciences, Applied Mathematics and Computation, Boletín de la Sociedad Matemática Mexicana, Animals 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.