Marcell Nagy

587 total citations
15 papers, 210 citations indexed

About

Marcell Nagy is a scholar working on Artificial Intelligence, Computer Science Applications and Statistical and Nonlinear Physics. According to data from OpenAlex, Marcell Nagy has authored 15 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 5 papers in Computer Science Applications and 3 papers in Statistical and Nonlinear Physics. Recurrent topics in Marcell Nagy's work include Online Learning and Analytics (5 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Complex Network Analysis Techniques (3 papers). Marcell Nagy is often cited by papers focused on Online Learning and Analytics (5 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Complex Network Analysis Techniques (3 papers). Marcell Nagy collaborates with scholars based in Hungary, Italy and Denmark. Marcell Nagy's co-authors include Roland Molontay, Péter Tamás Kovács, Katy Börner, Csaba Kiss, Aldo Ramírez-Arellano, Bruce W. Herr, Griffin M. Weber, Ellen M. Quardokus, Gyula Pályi and Béla Barabás and has published in prestigious journals such as Nature Communications, Assessment & Evaluation in Higher Education and Fractals.

In The Last Decade

Marcell Nagy

13 papers receiving 202 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcell Nagy Hungary 7 140 73 29 27 17 15 210
Gomathy Ramaswami New Zealand 7 168 1.2× 88 1.2× 43 1.5× 20 0.7× 18 1.1× 9 248
Therese Kanai United States 3 189 1.4× 46 0.6× 92 3.2× 13 0.5× 12 0.7× 4 250
Joshua D. Baron United States 6 287 2.0× 123 1.7× 120 4.1× 17 0.6× 33 1.9× 8 344
Nisha S. Raj India 7 140 1.0× 95 1.3× 32 1.1× 10 0.4× 10 0.6× 16 238
Samira ElAtia Canada 5 165 1.2× 98 1.3× 60 2.1× 31 1.1× 33 1.9× 15 240
Everaldo Aguiar United States 7 169 1.2× 125 1.7× 62 2.1× 20 0.7× 31 1.8× 10 275
Alfred Essa United States 7 195 1.4× 68 0.9× 62 2.1× 5 0.2× 18 1.1× 17 236
M. Anbarasan India 4 39 0.3× 127 1.7× 49 1.7× 4 0.1× 20 1.2× 7 210
Mahnane Lamia Algeria 7 76 0.5× 69 0.9× 99 3.4× 3 0.1× 19 1.1× 32 229
Weijie Jiang China 6 112 0.8× 250 3.4× 17 0.6× 3 0.1× 4 0.2× 10 328

Countries citing papers authored by Marcell Nagy

Since Specialization
Citations

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

Fields of papers citing papers by Marcell Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcell Nagy

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

All Works

15 of 15 papers shown
1.
Börner, Katy, Bruce W. Herr, Ellen M. Quardokus, et al.. (2025). Functional tissue units in the Human Reference Atlas. Nature Communications. 16(1). 1526–1526. 3 indexed citations
2.
Kiss, Csaba, et al.. (2025). Max–Min semantic chunking of documents for RAG application. Discover Computing. 28(1). 1 indexed citations
3.
Barabás, Béla, et al.. (2024). Progress in the valorization of biomass: a statistical perspective. Journal of Mathematical Chemistry. 62(5). 951–972.
4.
Nagy, Marcell, et al.. (2024). Topicality boosts popularity: a comparative analysis of NYT articles and Reddit memes. Social Network Analysis and Mining. 14(1). 3 indexed citations
5.
Nagy, Marcell, et al.. (2024). COMPLEX NETWORK CLASSIFICATION USING DENG ENTROPY AND BIDIRECTIONAL LONG SHORT-TERM MEMORY. Fractals. 33(1). 1 indexed citations
6.
7.
Nagy, Marcell & Roland Molontay. (2023). Interpretable Dropout Prediction: Towards XAI-Based Personalized Intervention. International Journal of Artificial Intelligence in Education. 34(2). 274–300. 38 indexed citations
8.
Nagy, Marcell, et al.. (2023). Towards a better understanding of the characteristics of fractal networks. Applied Network Science. 8(1). 3 indexed citations
9.
Nagy, Marcell & Roland Molontay. (2022). Network classification-based structural analysis of real networks and their model-generated counterparts. Network Science. 10(2). 146–169. 4 indexed citations
10.
Molontay, Roland & Marcell Nagy. (2022). How to improve the predictive validity of a composite admission score? A case study from Hungary. Assessment & Evaluation in Higher Education. 48(4). 419–437. 7 indexed citations
11.
Nagy, Marcell & Roland Molontay. (2021). Comprehensive analysis of the predictive validity of the university entrance score in Hungary. Assessment & Evaluation in Higher Education. 46(8). 1235–1253. 14 indexed citations
12.
Kovács, Péter Tamás, Marcell Nagy, & Roland Molontay. (2021). Comparative analysis of box-covering algorithms for fractal networks. Applied Network Science. 6(1). 13 indexed citations
13.
Nagy, Marcell, et al.. (2020). Interpretable Deep Learning for University Dropout Prediction. 13–19. 47 indexed citations
14.
Nagy, Marcell, et al.. (2019). Predicting Dropout Using High School and First-semester Academic Achievement Measures. 383–389. 19 indexed citations
15.
Nagy, Marcell & Roland Molontay. (2018). Predicting Dropout in Higher Education Based on Secondary School Performance. 389–394. 57 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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