Mau-Hsiang Shih

742 citations
50 papers · 518 indexed · h-index 13
Topics
Optimization and Variational Analysis (10 papers)Matrix Theory and Algorithms (7 papers)Neural dynamics and brain function (5 papers)
Partner nations
TaiwanCanadaFrance

In The Last Decade

Mau-Hsiang Shih

46 papers receiving 426 citations

Peers

Mau-Hsiang Shih
Comparison fields: 5 of 51
  • Computational Theory and Mathematics 326
  • Geometry and Topology 130
  • Applied Mathematics 105
  • Control and Systems Engineering 82
  • Numerical Analysis 76
Replace R. B. Bapat with:
R. B. Bapat India
Miroslav Bačák Germany
Jorma K. Merikoski Finland
Jean-Bernard Baillon France
D. H. Martin South Africa
Robert Reams United States
Helge Tverberg Norway
Kevin A. Grasse United States
Nicolai Vorobjov United Kingdom
Motakuri V. Ramana United States
Mau-Hsiang Shih relative to R. B. Bapat India R. B. Bapat's profile →
Citations per field
00.5×3.4×
R. B. Bapat · 1×
Citations per year

Countries citing papers authored by Mau-Hsiang Shih

Since Specialization
Citations

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

Fields of papers citing papers by Mau-Hsiang Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mau-Hsiang Shih. 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 Mau-Hsiang Shih. The network helps show where Mau-Hsiang Shih may publish in the future.

Co-authorship network of co-authors of Mau-Hsiang Shih

This figure shows the co-authorship network connecting the top 25 collaborators of Mau-Hsiang Shih. A scholar is included among the top collaborators of Mau-Hsiang Shih 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 Mau-Hsiang Shih. Mau-Hsiang Shih is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 6
4 1
5 0
6
A structure theorem for coupled balanced games without side payments(Nonlinear Analysis and Convex Analysis)
0
7 33
8 2
9 17
10 13
11 3
12 60
13 1
14 8
15 24
16 57
17 2
18 79
19 1
20 12

About Mau-Hsiang Shih

Mau-Hsiang Shih is a scholar working on Theoretical Computer Science, Geometry and Topology and Computational Theory and Mathematics, having authored 50 papers that have together received 518 indexed citations. Recurring topics across this work include Optimization and Variational Analysis (10 papers), Matrix Theory and Algorithms (7 papers) and Neural dynamics and brain function (5 papers). The work is most often cited by research in Computational Theory and Mathematics (326 citations), Geometry and Topology (130 citations) and Numerical Analysis (76 citations). Mau-Hsiang Shih has collaborated with scholars based in Taiwan, Canada and France. Frequent co-authors include Kok-Keong Tan, Chin-Tzong Pang, Tsuyoshi Andô, Cheh‐Chih Yeh, Pierre Meyrand and Tiaza Bem. Their work appears in journals such as Scientific Reports, Automatica and IEEE Transactions on Neural Networks and Learning Systems.

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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