Celine Vens
- Sensory Systems top 5%
- Artificial Intelligence top 2%
- Text and Document Classification Technologies 13
- Machine Learning and Data Classification 10
- Information Systems top 2%
- Data Mining Algorithms and Applications 11
- Recommender Systems and Techniques 5
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- Machine Learning in Bioinformatics 11
- Bioinformatics and Genomic Networks 9
- Genomics and Phylogenetic Studies 8
- RNA and protein synthesis mechanisms 5
- Co-authors
- Sašo DžeroskiJan StruyfHendrik BlockeelLeander SchietgatKonstantinos PliakosDragi KocevFabrizio CostaÉtienne Danchin
- Partner nations
- BelgiumNetherlandsSlovenia
In The Last Decade
Celine Vens
68 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 163
- Sensory Systems 143
- Artificial Intelligence 831
- Computational Theory and Mathematics 253
- Information Systems 270
- Computer Science Applications 64
Countries citing papers authored by Celine Vens
This map shows the geographic impact of Celine Vens'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 Celine Vens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Celine Vens more than expected).
Fields of papers citing papers by Celine Vens
This network shows the impact of papers produced by Celine Vens. 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 Celine Vens. The network helps show where Celine Vens may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Celine Vens, 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 | 2025 | 2 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 6 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 2 | |
| 8 | 2022 | 2 | |
| 9 | 2022 | 47 | |
| 10 | 2022 | 11 | |
| 11 | 2021 | 9 | |
| 12 | 2020 | 56 | |
| 13 | 2020 | 1 | |
| 14 | 2020 | 19 | |
| 15 | 2019 | 33 | |
| 16 | 2018 | 14 | |
| 17 | Teaching for Versus Through Problem Solving: Impact on Teaching and Learning. | 2018 | 1 |
| 18 | 2018 | 24 | |
| 19 | Identifying proteins involved in parasitism by discovering degenerated motifs | 2010 | 2 |
| 20 | Applying predictive clustering trees to the inductive logic programming 2005 challenge data | 2005 | 1 |
About Celine Vens
Celine Vens is a scholar working on Artificial Intelligence, Information Systems, Transplantation, Computational Theory and Mathematics and Computer Science Applications, having authored 73 papers that have together received 1.8k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (13 papers), Machine Learning in Bioinformatics (11 papers), Data Mining Algorithms and Applications (11 papers), Machine Learning and Data Classification (10 papers), Bioinformatics and Genomic Networks (9 papers), Genomics and Phylogenetic Studies (8 papers), Recommender Systems and Techniques (5 papers) and RNA and protein synthesis mechanisms (5 papers). The work is most often cited by research in Sensory Systems (143 citations), Artificial Intelligence (831 citations), Computational Theory and Mathematics (253 citations), Information Systems (270 citations) and Computer Science Applications (64 citations). Celine Vens has collaborated with scholars based in Belgium, Netherlands and Slovenia. Frequent co-authors include Sašo Džeroski, Jan Struyf, Hendrik Blockeel, Leander Schietgat, Konstantinos Pliakos, Dragi Kocev, Fabrizio Costa, Étienne Danchin, Marie‐Noëlle Rosso and Isaac Triguero. Their work appears in journals such as IEEE Access, Machine Learning, BMC Bioinformatics, Pattern Recognition and Bioinformatics.
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.