Jan Schepers
Impact in
- Computational Mathematics top 10%
-
- Psychometric Methodologies and Testing
Papers in
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- Advanced Clustering Algorithms Research 9
- Bayesian Methods and Mixture Models 3
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- Tensor decomposition and applications 3
- Co-authors
- Iven Van Mechelen (8 shared papers)Rianne Janssen (1 shared paper)Eva Ceulemans (3 shared papers)Gerjo Kok (4 shared papers)Madelon L. Peters (5 shared papers)Hans‐Fritz Gramke (4 shared papers)Rob A. C. Ruiter (4 shared papers)Maurice Theunissen (4 shared papers)
- Journals
- Journal of Classification (4 papers)BioMed Research International (2 papers)Behavior Research Methods (2 papers)Computational Statistics & Data Analysis (2 papers)Medicine (2 papers)
- Partner nations
- NetherlandsBelgiumSouth Africa
In The Last Decade
Jan Schepers
40 papers receiving 594 citations
Peers
Comparison fields: 5 of 95
- Computational Mathematics 9
- Management Science and Operations Research 78
- Safety, Risk, Reliability and Quality 40
- Obstetrics and Gynecology 26
- Spectroscopy 36
Countries citing papers authored by Jan Schepers
This map shows the geographic impact of Jan Schepers'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 Jan Schepers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Schepers more than expected).
Fields of papers citing papers by Jan Schepers
This network shows the impact of papers produced by Jan Schepers. 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 Jan Schepers. The network helps show where Jan Schepers may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Schepers, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 78 | |
| 2 | 2016 | 52 | |
| 3 | 2008 | 42 | |
| 4 | 2011 | 42 | |
| 5 | 2018 | 42 | |
| 6 | 2018 | 35 | |
| 7 | 2009 | 27 | |
| 8 | 2006 | 24 | |
| 9 | 2017 | 22 | |
| 10 | 2017 | 18 | |
| 11 | 2019 | 17 | |
| 12 | 2022 | 17 | |
| 13 | 2014 | 16 | |
| 14 | 2023 | 16 | |
| 15 | 2013 | 15 | |
| 16 | 2015 | 14 | |
| 17 | 2015 | 13 | |
| 18 | 2011 | 11 | |
| 19 | 2007 | 10 | |
| 20 | 2017 | 10 |
About Jan Schepers
Jan Schepers is a scholar working on Artificial Intelligence, Computational Mathematics, Epidemiology, Applied Psychology and Physiology, having authored 44 papers that have together received 620 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (9 papers), Traumatic Brain Injury Research (4 papers), Tensor decomposition and applications (3 papers), Anesthesia and Pain Management (3 papers), Sexual function and dysfunction studies (3 papers), Bayesian Methods and Mixture Models (3 papers), Smoking Behavior and Cessation (2 papers) and Behavioral Health and Interventions (2 papers). The work is most often cited by research in Computational Mathematics (9 citations), Management Science and Operations Research (78 citations), Safety, Risk, Reliability and Quality (40 citations), Obstetrics and Gynecology (26 citations) and Spectroscopy (36 citations). Jan Schepers has collaborated with scholars based in Netherlands, Belgium and South Africa. Frequent co-authors include Iven Van Mechelen, Rianne Janssen, Eva Ceulemans, Gerjo Kok, Madelon L. Peters, Hans‐Fritz Gramke, Rob A. C. Ruiter, Maurice Theunissen, Marco A. E. Marcus and Joeri Hofmans. Their work appears in journals such as Journal of Classification, BioMed Research International, Behavior Research Methods, Computational Statistics & Data Analysis and Medicine.
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.