Edwin Vans
Impact in
- Artificial Intelligence top 10%
- Machine Learning and Data Classification
- Neural Networks and Applications
Papers in
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- Control and Dynamics of Mobile Robots 2
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- Gene expression and cancer classification 2
- Single-cell and spatial transcriptomics 2
- Bioinformatics and Genomic Networks 1
- Co-authors
- Alok K. Sharma (5 shared papers)Keith A. Boroevich (2 shared papers)Tatsuhiko Tsunoda (3 shared papers)Daichi Shigemizu (2 shared papers)Artem Lysenko (1 shared paper)Ashwini Patil (2 shared papers)Ronesh Sharma (1 shared paper)Shiu Kumar (1 shared paper)
- Journals
- Briefings in Bioinformatics (2 papers)Scientific Reports (1 paper)Lecture notes in computer science (1 paper)International journal of Computer Networks & Communications (1 paper)
In The Last Decade
Edwin Vans
6 papers receiving 402 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 105
- Health Informatics 7
- Molecular Biology 126
- Computer Vision and Pattern Recognition 45
- Computational Mathematics 1
Countries citing papers authored by Edwin Vans
This map shows the geographic impact of Edwin Vans'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 Edwin Vans with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edwin Vans more than expected).
Fields of papers citing papers by Edwin Vans
This network shows the impact of papers produced by Edwin Vans. 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 Edwin Vans. The network helps show where Edwin Vans may publish in the future.
Co-authors
The 8 scholars most cited alongside Edwin Vans, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 303 | |
| 2 | 2021 | 55 | |
| 3 | 2016 | 19 | |
| 4 | 2020 | 19 | |
| 5 | 2014 | 15 | |
| 6 | 2019 | 3 | |
| 7 | 2013 | 0 |
About Edwin Vans
Edwin Vans is a scholar working on Control and Systems Engineering, Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 7 papers that have together received 414 indexed citations. Recurring topics across this work include Gene expression and cancer classification (2 papers), Control and Dynamics of Mobile Robots (2 papers), Single-cell and spatial transcriptomics (2 papers), Bioinformatics and Genomic Networks (1 paper), Neural Networks and Applications (1 paper), Fuzzy Logic and Control Systems (1 paper), Advanced Neural Network Applications (1 paper) and Indoor and Outdoor Localization Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (105 citations), Health Informatics (7 citations), Molecular Biology (126 citations), Computer Vision and Pattern Recognition (45 citations) and Computational Mathematics (1 citation). Edwin Vans has collaborated with scholars based in Fiji, Japan and Australia. Frequent co-authors include Alok K. Sharma, Keith A. Boroevich, Tatsuhiko Tsunoda, Daichi Shigemizu, Artem Lysenko, Ashwini Patil, Ronesh Sharma and Shiu Kumar. Their work appears in journals such as Briefings in Bioinformatics, Scientific Reports, Lecture notes in computer science and International journal of Computer Networks & Communications.
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.