Mohamed Wahib
- Artificial Intelligence top 10%
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Co-authors
- Naoya MaruyamaMasaharu MunetomoAsim MunawarKiyoshi AkamaTruong Thao NguyenRyousei TakanoSatoshi MatsuokaJens Domke
- Topics
- Parallel Computing and Optimization Techniques (22 papers)Advanced Neural Network Applications (13 papers)Distributed and Parallel Computing Systems (11 papers)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Mohamed Wahib
50 papers receiving 380 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 139
- Hardware and Architecture 124
- Computer Networks and Communications 122
- Computer Vision and Pattern Recognition 88
- Electrical and Electronic Engineering 54
Countries citing papers authored by Mohamed Wahib
This map shows the geographic impact of Mohamed Wahib'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 Mohamed Wahib with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Wahib more than expected).
Fields of papers citing papers by Mohamed Wahib
This network shows the impact of papers produced by Mohamed Wahib. 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 Mohamed Wahib. The network helps show where Mohamed Wahib may publish in the future.
Co-authorship network of co-authors of Mohamed Wahib
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Wahib. A scholar is included among the top collaborators of Mohamed Wahib 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 Mohamed Wahib. Mohamed Wahib is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 9 | |
| 8 | 3 | |
| 9 | 5 | |
| 10 | 8 | |
| 11 | 1 | |
| 12 | 17 | |
| 13 | 6 | |
| 14 | 11 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 8 | |
| 18 | 12 | |
| 19 | A Grid based Unified Framework for Optimization | 1 |
| 20 | 2 |
About Mohamed Wahib
Mohamed Wahib is a scholar working on Hardware and Architecture, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 403 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (22 papers), Advanced Neural Network Applications (13 papers) and Distributed and Parallel Computing Systems (11 papers). The work is most often cited by research in Hardware and Architecture (124 citations), Computer Networks and Communications (122 citations) and Computational Mathematics (3 citations). Mohamed Wahib has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Naoya Maruyama, Masaharu Munetomo, Asim Munawar, Kiyoshi Akama, Truong Thao Nguyen, Ryousei Takano, Satoshi Matsuoka, Jens Domke, Peng Chen and Aleksandr Drozd. Their work appears in journals such as Information Sciences, IEEE Transactions on Evolutionary Computation and Applied Soft Computing.
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.