Javier Andreu-Pérez

4.5k total citations · 2 hit papers
77 papers, 2.9k citations indexed

About

Javier Andreu-Pérez is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Javier Andreu-Pérez has authored 77 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 33 papers in Cognitive Neuroscience and 12 papers in Cellular and Molecular Neuroscience. Recurrent topics in Javier Andreu-Pérez's work include EEG and Brain-Computer Interfaces (28 papers), Fuzzy Logic and Control Systems (13 papers) and Neuroscience and Neural Engineering (12 papers). Javier Andreu-Pérez is often cited by papers focused on EEG and Brain-Computer Interfaces (28 papers), Fuzzy Logic and Control Systems (13 papers) and Neuroscience and Neural Engineering (12 papers). Javier Andreu-Pérez collaborates with scholars based in United Kingdom, Spain and Peru. Javier Andreu-Pérez's co-authors include Guang‐Zhong Yang, Benny Lo, Fani Deligianni, Daniele Ravì, Melissa Berthelot, Charence Wong, Stephen T.C. Wong, Carmen C. Y. Poon, Robert Merrifield and Daniel Leff and has published in prestigious journals such as NeuroImage, Neuroscience & Biobehavioral Reviews and IEEE Access.

In The Last Decade

Javier Andreu-Pérez

71 papers receiving 2.8k citations

Hit Papers

Deep Learning for Health Informatics 2015 2026 2018 2022 2016 2015 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Javier Andreu-Pérez United Kingdom 18 885 510 482 458 359 77 2.9k
Giuseppe De Pietro Italy 32 1.7k 1.9× 481 0.9× 366 0.8× 445 1.0× 698 1.9× 211 4.4k
M. Shamim Kaiser Bangladesh 32 1.1k 1.3× 436 0.9× 427 0.9× 361 0.8× 511 1.4× 191 3.9k
Damodar Reddy Edla India 29 959 1.1× 371 0.7× 418 0.9× 224 0.5× 243 0.7× 166 2.8k
Manolis Tsiknakis Greece 30 683 0.8× 586 1.1× 229 0.5× 617 1.3× 654 1.8× 240 4.0k
Fani Deligianni United Kingdom 18 565 0.6× 453 0.9× 529 1.1× 474 1.0× 533 1.5× 57 2.4k
Maysam Abbod United Kingdom 36 1.2k 1.3× 654 1.3× 372 0.8× 634 1.4× 440 1.2× 330 5.0k
Charence Wong United Kingdom 10 679 0.8× 145 0.3× 341 0.7× 511 1.1× 597 1.7× 20 2.1k
Andrés Ortíz Spain 29 787 0.9× 464 0.9× 338 0.7× 154 0.3× 489 1.4× 130 2.8k
Mohamed Hammad Egypt 28 822 0.9× 580 1.1× 463 1.0× 525 1.1× 494 1.4× 78 2.8k
Afshin Shoeibi Iran 29 836 0.9× 1.0k 2.0× 662 1.4× 191 0.4× 562 1.6× 60 2.9k

Countries citing papers authored by Javier Andreu-Pérez

Since Specialization
Citations

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

Fields of papers citing papers by Javier Andreu-Pérez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Javier Andreu-Pérez. 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 Javier Andreu-Pérez. The network helps show where Javier Andreu-Pérez may publish in the future.

Co-authorship network of co-authors of Javier Andreu-Pérez

This figure shows the co-authorship network connecting the top 25 collaborators of Javier Andreu-Pérez. A scholar is included among the top collaborators of Javier Andreu-Pérez 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 Javier Andreu-Pérez. Javier Andreu-Pérez 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.
Andreu-Pérez, Javier, et al.. (2025). Fuzzychain: An equitable consensus mechanism for blockchain networks. Journal of Network and Computer Applications. 241. 104204–104204.
3.
Andreu-Pérez, Javier, et al.. (2024). Transfer Learning With Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-Centre Data. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 3794–3803. 2 indexed citations
4.
5.
Andreu-Pérez, Javier, et al.. (2024). Finding neural correlates of depersonalisation/derealisation disorder via explainable CNN-based analysis guided by clinical assessment scores. Artificial Intelligence in Medicine. 149. 102755–102755. 1 indexed citations
6.
Andreu-Pérez, Javier, et al.. (2023). Toward assessment of human voice biomarkers of brain lesions through explainable deep learning. Biomedical Signal Processing and Control. 87. 105457–105457. 6 indexed citations
7.
Vidaurre, Carmen, Javier Fernández, Marisol Gómez, et al.. (2023). Supervised penalty-based aggregation applied to motor-imagery based brain-computer-interface. Pattern Recognition. 145. 109924–109924. 4 indexed citations
9.
Andreu-Pérez, Javier, et al.. (2022). Towards Understanding Human Functional Brain Development With Explainable Artificial Intelligence: Challenges and Perspectives. IEEE Computational Intelligence Magazine. 17(1). 16–33. 13 indexed citations
11.
Ding, Weiping, et al.. (2021). Fuzzy temporal convolutional neural networks in P300-based Brain–computer interface for smart home interaction. Applied Soft Computing. 117. 108359–108359. 26 indexed citations
12.
Andreu-Pérez, Javier, et al.. (2021). Single-Trial Recognition of Video Gamer’s Expertise from Brain Haemodynamic and Facial Emotion Responses. Brain Sciences. 11(1). 106–106. 15 indexed citations
13.
Andreu-Pérez, Javier, et al.. (2021). Explainable artificial intelligence based analysis for interpreting infant fNIRS data in developmental cognitive neuroscience. Communications Biology. 4(1). 1077–1077. 18 indexed citations
14.
Malik, Ali, et al.. (2020). Intelligent SDN Traffic Classification Using Deep Learning: Deep-SDN. Arrow - TU Dublin (Technological University Dublin). 184–189. 28 indexed citations
15.
Andreu-Pérez, Javier, et al.. (2020). Towards Decoding of Depersonalisation Disorder Using EEG: A Time Series Analysis Using CDTW. 548–553. 2 indexed citations
16.
Flores-Muñoz, V. H., et al.. (2018). A Convolutional Neural Network Approach for a P300-based Brain-Computer Interface for Disabled and Healthy Subjects. 3696. 192–197. 2 indexed citations
17.
Andreu-Pérez, Javier, et al.. (2017). Developing Fine-Grained Actigraphies for Rheumatoid Arthritis Patients from a Single Accelerometer Using Machine Learning. Sensors. 17(9). 2113–2113. 16 indexed citations
18.
Andreu-Pérez, Javier, Daniel Leff, Kunal Shetty, Ara Darzi, & Guang‐Zhong Yang. (2016). Disparity in Frontal Lobe Connectivity on a Complex Bimanual Motor Task Aids in Classification of Operator Skill Level. Brain Connectivity. 6(5). 375–388. 37 indexed citations
19.
Andreu-Pérez, Javier, Carmen C. Y. Poon, Robert Merrifield, Stephen T.C. Wong, & Guang‐Zhong Yang. (2015). Big Data for Health. IEEE Journal of Biomedical and Health Informatics. 19(4). 1193–1208. 446 indexed citations breakdown →
20.
Andreu-Pérez, Javier, et al.. (2011). Intelligent leader follower behaviour for unmanned ground-based vehicles. Journal of Automation Mobile Robotics & Intelligent Systems. 36–46. 2 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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