Tim Wilkin
Impact in
- Statistics and Probability top 2%
- Fuzzy Systems and Optimization
- Advanced Statistical Methods and Models
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- Multi-Criteria Decision Making
Papers in
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- Multi-Criteria Decision Making 14
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- Fuzzy Systems and Optimization 11
- Advanced Statistical Methods and Models 8
- Co-authors
- Gleb Beliakov (19 shared papers)Maia Angelova (6 shared papers)Anuroop Gaddam (3 shared papers)Tomasa Calvo (5 shared papers)Miguel Pagola (1 shared paper)Patrick J. Owen (3 shared papers)Daniel L. Belavý (3 shared papers)Simon James (7 shared papers)
In The Last Decade
Tim Wilkin
32 papers receiving 489 citations
Peers
Comparison fields: 5 of 96
- Statistics and Probability 160
- Management Science and Operations Research 231
- Health Informatics 15
- Artificial Intelligence 152
- Computational Theory and Mathematics 74
Countries citing papers authored by Tim Wilkin
This map shows the geographic impact of Tim Wilkin'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 Tim Wilkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Wilkin more than expected).
Fields of papers citing papers by Tim Wilkin
This network shows the impact of papers produced by Tim Wilkin. 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 Tim Wilkin. The network helps show where Tim Wilkin may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Wilkin, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 107 | |
| 2 | 2014 | 95 | |
| 3 | 2020 | 62 | |
| 4 | 2014 | 46 | |
| 5 | 2014 | 24 | |
| 6 | 2019 | 21 | |
| 7 | 2014 | 19 | |
| 8 | 2017 | 14 | |
| 9 | 2013 | 13 | |
| 10 | 2014 | 13 | |
| 11 | 2016 | 12 | |
| 12 | 2014 | 12 | |
| 13 | 2022 | 9 | |
| 14 | 2016 | 8 | |
| 15 | On weak monotonicity of some mixture functions | 2014 | 5 |
| 16 | 2019 | 5 | |
| 17 | 2018 | 5 | |
| 18 | 2017 | 4 | |
| 19 | 2014 | 4 | |
| 20 | 2023 | 3 |
About Tim Wilkin
Tim Wilkin is a scholar working on Management Science and Operations Research, Statistics and Probability, Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics, having authored 33 papers that have together received 500 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (14 papers), Fuzzy Systems and Optimization (11 papers), Advanced Statistical Methods and Models (8 papers), Rough Sets and Fuzzy Logic (4 papers), Data Management and Algorithms (3 papers), Image Retrieval and Classification Techniques (3 papers), Remote-Sensing Image Classification (3 papers) and Musculoskeletal pain and rehabilitation (3 papers). The work is most often cited by research in Statistics and Probability (160 citations), Management Science and Operations Research (231 citations), Health Informatics (15 citations), Artificial Intelligence (152 citations) and Computational Theory and Mathematics (74 citations). Tim Wilkin has collaborated with scholars based in Australia, Spain and Germany. Frequent co-authors include Gleb Beliakov, Maia Angelova, Anuroop Gaddam, Tomasa Calvo, Miguel Pagola, Patrick J. Owen, Daniel L. Belavý, Simon James, Clint T. Miller and Scott D. Tagliaferri. Their work appears in journals such as Information Sciences, Scientific Reports, Knowledge-Based Systems, IEEE Transactions on Fuzzy Systems and Electronics.
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.