Ruxandra Stoean

1.6k total citations
71 papers, 929 citations indexed

About

Ruxandra Stoean is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Epidemiology. According to data from OpenAlex, Ruxandra Stoean has authored 71 papers receiving a total of 929 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 8 papers in Epidemiology. Recurrent topics in Ruxandra Stoean's work include Evolutionary Algorithms and Applications (20 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Neural Networks and Applications (6 papers). Ruxandra Stoean is often cited by papers focused on Evolutionary Algorithms and Applications (20 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Neural Networks and Applications (6 papers). Ruxandra Stoean collaborates with scholars based in Romania, Spain and Serbia. Ruxandra Stoean's co-authors include Cătălin Stoean, Mike Preuß, Nebojša Bačanin, Miodrag Živković, D. Dumitrescu, Aleksandar Petrović, Tarik A. Rashid, Timea Bezdan, Roma Strulak-Wójcikiewicz and Adriana Samide and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Sensors.

In The Last Decade

Ruxandra Stoean

62 papers receiving 898 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ruxandra Stoean Romania 16 496 132 123 120 80 71 929
Cătălin Stoean Romania 19 602 1.2× 150 1.1× 120 1.0× 124 1.0× 92 1.1× 75 1.1k
Jacek M. Zurada United States 12 564 1.1× 110 0.8× 79 0.6× 147 1.2× 43 0.5× 37 1.0k
Changfei Tong China 9 635 1.3× 112 0.8× 147 1.2× 126 1.1× 28 0.3× 16 1.1k
Waleed M. Mohamed Egypt 13 542 1.1× 137 1.0× 230 1.9× 90 0.8× 78 1.0× 23 931
Aaron Klein Germany 8 753 1.5× 92 0.7× 129 1.0× 236 2.0× 76 0.9× 25 1.2k
Rania M. Ghoniem Saudi Arabia 17 426 0.9× 143 1.1× 111 0.9× 120 1.0× 27 0.3× 46 859
Prachi Agrawal India 12 529 1.1× 99 0.8× 158 1.3× 220 1.8× 32 0.4× 39 967
Mahdi Eftekhari Iran 23 590 1.2× 101 0.8× 181 1.5× 259 2.2× 84 1.1× 135 1.5k

Countries citing papers authored by Ruxandra Stoean

Since Specialization
Citations

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

Fields of papers citing papers by Ruxandra Stoean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruxandra Stoean

This figure shows the co-authorship network connecting the top 25 collaborators of Ruxandra Stoean. A scholar is included among the top collaborators of Ruxandra Stoean 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 Ruxandra Stoean. Ruxandra Stoean 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.
Petrović, Aleksandar, et al.. (2025). Evaluation Performance of Metaheuristics-Tuned Convolutional Neural Networks for Direct Current Motor Using Mel Spectrograms. Arabian Journal for Science and Engineering. 1 indexed citations
2.
3.
Stoean, Ruxandra, et al.. (2024). Bridging the past and present: AI-driven 3D restoration of degraded artefacts for museum digital display. Journal of Cultural Heritage. 69. 18–26. 2 indexed citations
4.
Bačanin, Nebojša, Luka Jovanović, Ruxandra Stoean, et al.. (2024). Respiratory Condition Detection Using Audio Analysis and Convolutional Neural Networks Optimized by Modified Metaheuristics. Axioms. 13(5). 335–335. 18 indexed citations
5.
6.
Bačanin, Nebojša, et al.. (2023). On the Benefits of Using Metaheuristics in the Hyperparameter Tuning of Deep Learning Models for Energy Load Forecasting. Energies. 16(3). 1434–1434. 67 indexed citations
7.
Jovanović, Luka, Nebojša Bačanin, Cătălin Stoean, et al.. (2023). Applying Recurrent Neural Networks for Anomaly Detection in Electrocardiogram Sensor Data. Sensors. 23(24). 9878–9878. 25 indexed citations
8.
Stoean, Cătălin, Miodrag Živković, Nebojša Bačanin, et al.. (2023). Metaheuristic-Based Hyperparameter Tuning for Recurrent Deep Learning: Application to the Prediction of Solar Energy Generation. Axioms. 12(3). 266–266. 51 indexed citations
9.
Stoean, Ruxandra, et al.. (2023). Computational framework for the evaluation of the composition and degradation state of metal heritage assets by deep learning. Journal of Cultural Heritage. 64. 198–206. 6 indexed citations
10.
Tudorache, Ş., Panagiotis Antsaklis, G. Daskalakis, et al.. (2021). Sonographic Evaluation of the Mechanism of Active Labor (SonoLabor Study): observational study protocol regarding the implementation of the sonopartogram. BMJ Open. 11(9). e047188–e047188. 1 indexed citations
11.
Bačanin, Nebojša, Ruxandra Stoean, Miodrag Živković, et al.. (2021). Performance of a Novel Chaotic Firefly Algorithm with Enhanced Exploration for Tackling Global Optimization Problems: Application for Dropout Regularization. Mathematics. 9(21). 2705–2705. 134 indexed citations
12.
Stoean, Ruxandra, et al.. (2018). Non-negative Matrix Factorization for Medical Imaging.. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 1 indexed citations
13.
Iliescu, Dominic Gabriel, Ş. Tudorache, N. Cernea, et al.. (2017). P13.03: Correlations of the sonopartogram with classic clinical partogram and key points from a pilot study. Ultrasound in Obstetrics and Gynecology. 50(S1). 194–195. 1 indexed citations
14.
Stoean, Ruxandra & Florin Gorunescu. (2013). A Survey on Feature Ranking by Means of Evolutionary Computation. Annals of the University of Craiova Mathematics and Computer Science Series. 40(1). 100–105. 6 indexed citations
15.
Stoean, Ruxandra, Cătălin Stoean, Monica Lupșor‐Platon, Horia Ştefănescu, & Radu Badea. (2010). Evolutionary conditional rules versus support vector machines weighted formulas for liver fibrosis degree prediction. 37(1). 43–54. 1 indexed citations
16.
Stoean, Cătălin, Mike Preuß, & Ruxandra Stoean. (2009). Species Separation by a Clustering Mean towards Multimodal Function Optimization. Annals of the University of Craiova Mathematics and Computer Science Series. 36(2). 53–62.
17.
Stoean, Ruxandra, Mike Preuß, Cătălin Stoean, Elia El‐Darzi, & D. Dumitrescu. (2008). Support vector machine learning with an evolutionary engine. Journal of the Operational Research Society. 60(8). 1116–1122. 15 indexed citations
18.
Dumitrescu, D., Mike Preuß, Cătălin Stoean, & Ruxandra Stoean. (2008). Coevolution for classification. Technische Universität Dortmund Eldorado (Technische Universität Dortmund). 7 indexed citations
19.
Stoean, Ruxandra & D. Dumitrescu. (2006). Linear Evolutionary Support Vector Machines for Separable Training Data. Annals of the University of Craiova Mathematics and Computer Science Series. 33. 141–146. 1 indexed citations
20.
Stoean, Ruxandra, Cătălin Stoean, Mike Preuß, & D. Dumitrescu. (2006). Evolutionary Multi-class Support Vector Machines for Classification. International Journal of Computers Communications & Control. 1. 3 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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