Ioannis G. Tsoulos
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 2%
- Control and Systems Engineering top 10%
- Numerical Analysis top 5%
- Molecular Biology
- Co-authors
- Athanassios StavrakoudisDimitris GavrilisI.E. LagarisEuripidis GlavasAlexandros T. TzallasFardin Akhlaghian TabFardin AhmadizarChrysostomos Stylios
- Topics
- Metaheuristic Optimization Algorithms Research (50 papers)Evolutionary Algorithms and Applications (40 papers)Neural Networks and Applications (33 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsSensors
- Partner nations
- GreeceUnited KingdomUnited States
In The Last Decade
Ioannis G. Tsoulos
98 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 148
- Artificial Intelligence 587
- Computational Theory and Mathematics 206
- Control and Systems Engineering 108
- Numerical Analysis 105
- Molecular Biology 103
Countries citing papers authored by Ioannis G. Tsoulos
This map shows the geographic impact of Ioannis G. Tsoulos'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 Ioannis G. Tsoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ioannis G. Tsoulos more than expected).
Fields of papers citing papers by Ioannis G. Tsoulos
This network shows the impact of papers produced by Ioannis G. Tsoulos. 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 Ioannis G. Tsoulos. The network helps show where Ioannis G. Tsoulos may publish in the future.
Co-authorship network of co-authors of Ioannis G. Tsoulos
This figure shows the co-authorship network connecting the top 25 collaborators of Ioannis G. Tsoulos. A scholar is included among the top collaborators of Ioannis G. Tsoulos 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 Ioannis G. Tsoulos. Ioannis G. Tsoulos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | 3 | |
| 11 | 18 | |
| 12 | 11 | |
| 13 | 11 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 16 | |
| 18 | 4 | |
| 19 | 4 | |
| 20 | Neural splines: exploiting parallelism for function approximation using modular neural networks | 0 |
About Ioannis G. Tsoulos
Ioannis G. Tsoulos is a scholar working on Artificial Intelligence, Numerical Analysis and Computational Theory and Mathematics, having authored 117 papers that have together received 1.3k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (50 papers), Evolutionary Algorithms and Applications (40 papers) and Neural Networks and Applications (33 papers). The work is most often cited by research in Numerical Analysis (105 citations), Artificial Intelligence (587 citations) and Computational Theory and Mathematics (206 citations). Ioannis G. Tsoulos has collaborated with scholars based in Greece, United Kingdom and United States. Frequent co-authors include Athanassios Stavrakoudis, Dimitris Gavrilis, I.E. Lagaris, Euripidis Glavas, Alexandros T. Tzallas, Fardin Akhlaghian Tab, Fardin Ahmadizar, Chrysostomos Stylios, Evangelos Dermatas and Νικόλαος Γιαννακέας. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Sensors.
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.