Georgios Kostopoulos

972 total citations
23 papers, 573 citations indexed

About

Georgios Kostopoulos is a scholar working on Artificial Intelligence, Computer Science Applications and Computer Networks and Communications. According to data from OpenAlex, Georgios Kostopoulos has authored 23 papers receiving a total of 573 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 16 papers in Computer Science Applications and 4 papers in Computer Networks and Communications. Recurrent topics in Georgios Kostopoulos's work include Online Learning and Analytics (16 papers), Imbalanced Data Classification Techniques (10 papers) and Machine Learning and Data Classification (10 papers). Georgios Kostopoulos is often cited by papers focused on Online Learning and Analytics (16 papers), Imbalanced Data Classification Techniques (10 papers) and Machine Learning and Data Classification (10 papers). Georgios Kostopoulos collaborates with scholars based in Greece, Cyprus and United Kingdom. Georgios Kostopoulos's co-authors include Sotiris Kotsiantis, O. Ragos, Stamatis Karlos, Nikos Fazakis, Christos Pierrakeas, Panagiotis Pintelas, Achilles Kameas, Theodor Panagiotakopoulos, Iosif Mporas and Omiros Iatrellis and has published in prestigious journals such as IEEE Access, Applied Sciences and Electronics.

In The Last Decade

Georgios Kostopoulos

20 papers receiving 550 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Georgios Kostopoulos Greece 14 269 254 72 64 58 23 573
Bo Jiang China 13 132 0.5× 148 0.6× 85 1.2× 62 1.0× 16 0.3× 68 646
Tomáš Horváth Slovakia 14 120 0.4× 271 1.1× 173 2.4× 41 0.6× 15 0.3× 40 538
Stamatis Karlos Greece 10 64 0.2× 265 1.0× 49 0.7× 28 0.4× 19 0.3× 32 461
Yazan A. Alsariera Saudi Arabia 11 80 0.3× 170 0.7× 179 2.5× 127 2.0× 17 0.3× 31 449
Ashraf Y. A. Maghari Palestinian Territory 11 72 0.3× 185 0.7× 80 1.1× 34 0.5× 44 0.8× 35 434
Péricles Miranda Brazil 13 31 0.1× 295 1.2× 62 0.9× 34 0.5× 11 0.2× 70 504
Senthil Kumar Thangavel India 12 38 0.1× 134 0.5× 77 1.1× 89 1.4× 12 0.2× 83 443
T. V. Geetha India 9 41 0.2× 151 0.6× 89 1.2× 30 0.5× 9 0.2× 38 392
Abdul Hadi M. Alaidi Iraq 11 19 0.1× 74 0.3× 94 1.3× 61 1.0× 28 0.5× 22 457

Countries citing papers authored by Georgios Kostopoulos

Since Specialization
Citations

This map shows the geographic impact of Georgios Kostopoulos'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 Georgios Kostopoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georgios Kostopoulos more than expected).

Fields of papers citing papers by Georgios Kostopoulos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Georgios Kostopoulos. 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 Georgios Kostopoulos. The network helps show where Georgios Kostopoulos may publish in the future.

Co-authorship network of co-authors of Georgios Kostopoulos

This figure shows the co-authorship network connecting the top 25 collaborators of Georgios Kostopoulos. A scholar is included among the top collaborators of Georgios Kostopoulos 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 Georgios Kostopoulos. Georgios Kostopoulos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kostopoulos, Georgios, et al.. (2025). Agentic AI in Education: State of the Art and Future Directions. IEEE Access. 13. 177467–177491.
2.
3.
Kostopoulos, Georgios, et al.. (2024). Explainable Artificial Intelligence-Based Decision Support Systems: A Recent Review. Electronics. 13(14). 2842–2842. 20 indexed citations
4.
Panagiotakopoulos, Theodor, Sotiris Kotsiantis, Georgios Kostopoulos, Omiros Iatrellis, & Achilles Kameas. (2021). Early Dropout Prediction in MOOCs through Supervised Learning and Hyperparameter Optimization. Electronics. 10(14). 1701–1701. 25 indexed citations
5.
Kostopoulos, Georgios, et al.. (2021). Fuzzy-based active learning for predicting student academic performance using autoML: a step-wise approach. Journal of Computing in Higher Education. 33(3). 635–667. 18 indexed citations
6.
Kostopoulos, Georgios, Theodor Panagiotakopoulos, Sotiris Kotsiantis, Christos Pierrakeas, & Achilles Kameas. (2021). Interpretable Models for Early Prediction of Certification in MOOCs: A Case Study on a MOOC for Smart City Professionals. IEEE Access. 9. 165881–165891. 15 indexed citations
7.
Karlos, Stamatis, Georgios Kostopoulos, & Sotiris Kotsiantis. (2020). A Soft-Voting Ensemble Based Co-Training Scheme Using Static Selection for Binary Classification Problems. Algorithms. 13(1). 26–26. 47 indexed citations
8.
Karlos, Stamatis, Georgios Kostopoulos, & Sotiris Kotsiantis. (2020). Predicting and Interpreting Students’ Grades in Distance Higher Education through a Semi-Regression Method. Applied Sciences. 10(23). 8413–8413. 31 indexed citations
9.
Kostopoulos, Georgios, et al.. (2020). Fuzzy-based Active Learning for Predicting Student Academic Performance. 1–6. 4 indexed citations
10.
Fazakis, Nikos, Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, & Kyriakos Sgarbas. (2020). An active learning ensemble method for regression tasks. Intelligent Data Analysis. 24(3). 607–623. 2 indexed citations
11.
Kostopoulos, Georgios, et al.. (2020). Transfer Learning from Deep Neural Networks for Predicting Student Performance. Applied Sciences. 10(6). 2145–2145. 74 indexed citations
12.
Fazakis, Nikos, Georgios Kostopoulos, Sotiris Kotsiantis, & Iosif Mporas. (2020). Iterative Robust Semi-Supervised Missing Data Imputation. IEEE Access. 8. 90555–90569. 28 indexed citations
13.
Kostopoulos, Georgios, et al.. (2019). Implementing AutoML in Educational Data Mining for Prediction Tasks. Applied Sciences. 10(1). 90–90. 68 indexed citations
14.
Kostopoulos, Georgios, et al.. (2019). A Semi-Supervised Regression Algorithm for Grade Prediction of Students in Distance Learning Courses. International Journal of Artificial Intelligence Tools. 28(4). 1940001–1940001. 21 indexed citations
15.
Kostopoulos, Georgios, Nikos Fazakis, Sotiris Kotsiantis, & Kyriakos Sgarbas. (2019). Multi-objective Optimization of C4.5 Decision Tree for Predicting Student Academic Performance. 1–4. 6 indexed citations
16.
Kostopoulos, Georgios, Stamatis Karlos, & Sotiris Kotsiantis. (2019). Multiview Learning for Early Prognosis of Academic Performance: A Case Study. IEEE Transactions on Learning Technologies. 12(2). 212–224. 27 indexed citations
17.
Kostopoulos, Georgios, et al.. (2018). Predicting University Students' Grades Based on Previous Academic Achievements. 1–6. 21 indexed citations
18.
Kostopoulos, Georgios, et al.. (2017). Enhancing high school students' performance based on semi-supervised methods. 1–6. 3 indexed citations
19.
Kostopoulos, Georgios, et al.. (2017). Early dropout prediction in distance higher education using active learning. 1–6. 10 indexed citations
20.
Kostopoulos, Georgios, Sotiris Kotsiantis, & Panagiotis Pintelas. (2015). Estimating student dropout in distance higher education using semi-supervised techniques. 38–43. 31 indexed citations

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.

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