Arghir-Nicolae Moldovan

714 total citations
30 papers, 456 citations indexed

About

Arghir-Nicolae Moldovan is a scholar working on Sociology and Political Science, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Arghir-Nicolae Moldovan has authored 30 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Sociology and Political Science, 11 papers in Computer Vision and Pattern Recognition and 8 papers in Information Systems. Recurrent topics in Arghir-Nicolae Moldovan's work include Image and Video Quality Assessment (9 papers), Multimedia Communication and Technology (7 papers) and Green IT and Sustainability (5 papers). Arghir-Nicolae Moldovan is often cited by papers focused on Image and Video Quality Assessment (9 papers), Multimedia Communication and Technology (7 papers) and Green IT and Sustainability (5 papers). Arghir-Nicolae Moldovan collaborates with scholars based in Ireland, Brazil and France. Arghir-Nicolae Moldovan's co-authors include Cristina Hava Muntean, Ioana Ghergulescu, Stephan Weibelzahl, Pramod Pathak, Adriana E. Chis, Lisa Murphy, Gabriel‐Miro Muntean, Olga Ormond, Ramona Trestian and Irina Tal and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, Educational Technology & Society and IEEE Transactions on Broadcasting.

In The Last Decade

Arghir-Nicolae Moldovan

28 papers receiving 438 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arghir-Nicolae Moldovan Ireland 12 159 120 95 88 86 30 456
Ioana Ghergulescu Ireland 12 141 0.9× 53 0.4× 36 0.4× 59 0.7× 90 1.0× 37 426
Kamal Bijlani India 12 121 0.8× 45 0.4× 39 0.4× 30 0.3× 74 0.9× 50 442
Yuanchun Shi China 9 153 1.0× 79 0.7× 38 0.4× 37 0.4× 57 0.7× 21 397
Peter Parnes Sweden 12 126 0.8× 257 2.1× 49 0.5× 124 1.4× 19 0.2× 54 488
Chris Hancock United Kingdom 8 63 0.4× 37 0.3× 63 0.7× 35 0.4× 109 1.3× 11 564
Qifan Yang China 14 170 1.1× 30 0.3× 29 0.3× 38 0.4× 164 1.9× 21 757
Christopher Claus Germany 16 101 0.6× 117 1.0× 117 1.2× 90 1.0× 127 1.5× 30 603
Zachary Dodds United States 14 125 0.8× 26 0.2× 26 0.3× 31 0.4× 52 0.6× 59 560
Goffredo Haus Italy 11 233 1.5× 67 0.6× 25 0.3× 23 0.3× 23 0.3× 70 405
Cheng‐Yu Hung Taiwan 10 20 0.1× 43 0.4× 53 0.6× 32 0.4× 126 1.5× 24 395

Countries citing papers authored by Arghir-Nicolae Moldovan

Since Specialization
Citations

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

Fields of papers citing papers by Arghir-Nicolae Moldovan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arghir-Nicolae Moldovan. 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 Arghir-Nicolae Moldovan. The network helps show where Arghir-Nicolae Moldovan may publish in the future.

Co-authorship network of co-authors of Arghir-Nicolae Moldovan

This figure shows the co-authorship network connecting the top 25 collaborators of Arghir-Nicolae Moldovan. A scholar is included among the top collaborators of Arghir-Nicolae Moldovan 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 Arghir-Nicolae Moldovan. Arghir-Nicolae Moldovan 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.
Ghergulescu, Ioana, et al.. (2025). Malware Detection in PDF and PE Files Using Machine Learning and Feature Selection. 1–6. 1 indexed citations
2.
Moldovan, Arghir-Nicolae, et al.. (2023). A Novel Hybrid Machine Learning Framework to Recommend E-Commerce Products. 59–67. 2 indexed citations
3.
Ghergulescu, Ioana, et al.. (2022). Classification of Student Affective States in Online Learning using Neural Networks. 1–6. 3 indexed citations
4.
Moldovan, Arghir-Nicolae, et al.. (2021). Sensing Learner Interest Through Eye Tracking. Arrow - TU Dublin (Technological University Dublin).
5.
6.
Ghergulescu, Ioana, Arghir-Nicolae Moldovan, Cristina Hava Muntean, & Gabriel‐Miro Muntean. (2019). Atomic Structure Interactive Personalised Virtual Lab: Results from an Evaluation Study in Secondary Schools. NORMA. 605–615. 2 indexed citations
7.
Ghergulescu, Ioana, et al.. (2019). OULAD MOOC Dropout and Result Prediction using Ensemble, Deep Learning and Regression Techniques. NORMA. 28 indexed citations
8.
Ghergulescu, Ioana, et al.. (2019). A CASE STUDY IN STEM EDUCATION FOR LEARNERS WITH SPECIAL EDUCATION NEEDS. EDULEARN proceedings. 1. 10152–10157.
9.
Chis, Adriana E., Arghir-Nicolae Moldovan, Lisa Murphy, Pramod Pathak, & Cristina Hava Muntean. (2018). Investigating Flipped Classroom and Problem-based Learning in a Programming Module for Computing Conversion Course. Educational Technology & Society. 21(4). 232–247. 76 indexed citations
10.
Ghergulescu, Ioana, et al.. (2018). STEM EDUCATION WITH ATOMIC STRUCTURE VIRTUAL LAB FOR LEARNERS WITH SPECIAL EDUCATION NEEDS. EDULEARN proceedings. 18 indexed citations
11.
Moldovan, Arghir-Nicolae, Ioana Ghergulescu, & Cristina Hava Muntean. (2017). Analysis of Learner Interest, QoE and EEG-Based Affective States in Multimedia Mobile Learning. NORMA. 398–402. 11 indexed citations
12.
Moldovan, Arghir-Nicolae & Cristina Hava Muntean. (2017). QoE-aware video resolution thresholds computation for adaptive multimedia. 1–6. 13 indexed citations
13.
Moldovan, Arghir-Nicolae & Cristina Hava Muntean. (2016). User QoE assessment on mobile devices for natural and non-natural multimedia clips. 19. 1–5. 2 indexed citations
14.
Moldovan, Arghir-Nicolae, et al.. (2016). Gameplay Genre Video Classification by Using Mid-Level Video Representation. 188–194. 2 indexed citations
15.
Ghergulescu, Ioana, Arghir-Nicolae Moldovan, & Cristina Hava Muntean. (2015). Energy consumption analysis of cloud-based video games streaming to mobile devices. 10. 1–6. 2 indexed citations
16.
Moldovan, Arghir-Nicolae, Ioana Ghergulescu, & Cristina Hava Muntean. (2015). Performance evaluation of EMOS model for mapping-based Video Quality estimation. 24. 120–125. 4 indexed citations
17.
Moldovan, Arghir-Nicolae, Ioana Ghergulescu, & Cristina Hava Muntean. (2014). Educational Multimedia Profiling Recommendations for Device-aware Adaptive Mobile Learning. TRAP@NCI (National College of Ireland). 2014(1). 8 indexed citations
18.
Moldovan, Arghir-Nicolae, Stephan Weibelzahl, & Cristina Hava Muntean. (2014). Energy-Aware Mobile Learning:Opportunities and Challenges. IEEE Communications Surveys & Tutorials. 16(1). 234–265. 31 indexed citations
19.
Moldovan, Arghir-Nicolae, Ioana Ghergulescu, & Cristina Hava Muntean. (2014). A novel methodology for mapping objective video quality metrics to the subjective MOS scale. TRAP@NCI (National College of Ireland). 1–7. 24 indexed citations
20.
Trestian, Ramona, Arghir-Nicolae Moldovan, Cristina Hava Muntean, Olga Ormond, & Gabriel‐Miro Muntean. (2012). Quality Utility modelling for multimedia applications for Android Mobile devices. 1–6. 39 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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