M. W. Wong

2.1k citations
100 papers · 1.1k indexed · h-index 17

M. W. Wong

91 papers receiving 1.0k citations

Peers

M. W. Wong
Comparison fields: 5 of 62
  • Applied Mathematics 851
  • Mathematical Physics 552
  • Computer Vision and Pattern Recognition 239
  • Computational Theory and Mathematics 124
  • Signal Processing 72
Replace Fabio Nicola with:
Fabio Nicola Italy
Richard S. Laugesen United States
Aline Bonami France
Piotr Mikusiński United States
Khalifa Trimèche Tunisia
Eugenio Hernández Spain
Kristian Seip Norway
Elena Cordero Italy
Eric Weber United States
Pierre Gilles Lemarié–Rieusset France
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Citations per field
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Citations per year

Countries citing papers authored by M. W. Wong

Since Specialization
Citations

This map shows the geographic impact of M. W. Wong'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. W. Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. W. Wong more than expected).

Fields of papers citing papers by M. W. Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. W. Wong. 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. W. Wong. The network helps show where M. W. Wong may publish in the future.

Co-authorship network

The 25 scholars most cited alongside M. W. Wong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. W. Wong Line = papers co-authored together M. W. Wong links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20203
2 201423
3 201363
4 201014
5 201039
6
New developments in pseudo-differential operators : ISAAC Group in Pseudo-Differential Operators (IGPDO), Middle East Technical University, Ankara, Turkey, August 2007
20092
7 20096
8 20081
9 20085
10 200743
11 20079
12 200515
13 200234
14
Scanner - A tool for collecting object oriented software metrics from C++ class definitions
19981
15 199420
16 19911
17 19841
18 19810
19 19818
20 19802

About M. W. Wong

M. W. Wong is a scholar working on Mathematical Physics, Applied Mathematics and Computational Theory and Mathematics, having authored 100 papers that have together received 1.1k indexed citations. Recurring topics across this work include Mathematical Analysis and Transform Methods (56 papers), Spectral Theory in Mathematical Physics (39 papers), Advanced Mathematical Modeling in Engineering (27 papers), advanced mathematical theories (19 papers), Image and Signal Denoising Methods (15 papers), Numerical methods in inverse problems (14 papers), Advanced Harmonic Analysis Research (13 papers) and Differential Equations and Boundary Problems (8 papers). The work is most often cited by research in Applied Mathematics (851 citations), Mathematical Physics (552 citations) and Computer Vision and Pattern Recognition (239 citations). M. W. Wong has collaborated with scholars based in Canada, United Kingdom and Italy. Frequent co-authors include Paolo Boggiatto, Bert‐Wolfgang Schulze, Hongmei Zhu, Julio Delgado, Luigi Rodino, He Zhao, Hongmei Zhu, Yü Liu, Zhaohui Zhang and B.‐W. Schulze. Their work appears in journals such as Journal of Computational Chemistry, Journal of Mathematical Analysis and Applications and Theoretical Chemistry Accounts.

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.

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