Andreas Artemiou

588 total citations
39 papers, 354 citations indexed

About

Andreas Artemiou is a scholar working on Statistics and Probability, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Andreas Artemiou has authored 39 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Statistics and Probability, 12 papers in Computer Vision and Pattern Recognition and 11 papers in Artificial Intelligence. Recurrent topics in Andreas Artemiou's work include Face and Expression Recognition (11 papers), Statistical Methods and Inference (10 papers) and Sparse and Compressive Sensing Techniques (9 papers). Andreas Artemiou is often cited by papers focused on Face and Expression Recognition (11 papers), Statistical Methods and Inference (10 papers) and Sparse and Compressive Sensing Techniques (9 papers). Andreas Artemiou collaborates with scholars based in United Kingdom, United States and Cyprus. Andreas Artemiou's co-authors include Bing Li, Lexin Li, Dimitris Challoumas, Adrienne Minerick, Soumya K. Srivastava, Seung Jun Shin, Yuexiao Dong, Lowri Williams, ‪Irena Spasić and Michael Arribas‐Ayllon and has published in prestigious journals such as Bioinformatics, Pattern Recognition and The Annals of Statistics.

In The Last Decade

Andreas Artemiou

34 papers receiving 345 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andreas Artemiou United Kingdom 12 94 70 70 65 50 39 354
Hsin‐Hsiung Huang United States 9 10 0.1× 42 0.6× 18 0.3× 36 0.6× 5 0.1× 56 274
Norimasa Yoshida Japan 11 28 0.3× 15 0.2× 28 0.4× 50 0.8× 213 4.3× 42 401
Pascal Germain Canada 8 14 0.1× 166 2.4× 17 0.2× 72 1.1× 14 0.3× 19 259
Banghua Zhu United States 7 18 0.2× 93 1.3× 10 0.1× 15 0.2× 12 0.2× 15 189
R. U. Gobithaasan Malaysia 11 13 0.1× 23 0.3× 23 0.3× 49 0.8× 184 3.7× 65 348
Fabian Lim United States 8 10 0.1× 44 0.6× 46 0.7× 20 0.3× 52 1.0× 25 255
Munmun Biswas Bangladesh 10 107 1.1× 127 1.8× 4 0.1× 28 0.4× 7 0.1× 16 325
Murtaza Ali Khan Saudi Arabia 9 2 0.0× 68 1.0× 36 0.5× 99 1.5× 38 0.8× 22 334
Kaidi Cao United States 10 4 0.0× 184 2.6× 43 0.6× 364 5.6× 42 0.8× 18 519
Dong Yin China 8 5 0.1× 82 1.2× 9 0.1× 78 1.2× 43 0.9× 29 224

Countries citing papers authored by Andreas Artemiou

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Artemiou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Artemiou

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Artemiou. A scholar is included among the top collaborators of Andreas Artemiou 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 Andreas Artemiou. Andreas Artemiou 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.
Artemiou, Andreas, et al.. (2024). Least Squares Minimum Class Variance Support Vector Machines. Computers. 13(2). 34–34. 2 indexed citations
2.
Raffray, Loïc, Simone Cuff, Daniel A. White, et al.. (2024). Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients. Clinical & Experimental Immunology. 216(3). 293–306. 5 indexed citations
3.
Artemiou, Andreas, et al.. (2023). Adaptive L0 Regularization for Sparse Support Vector Regression. Mathematics. 11(13). 2808–2808. 1 indexed citations
4.
Cuff, Simone, et al.. (2022). GeoWaVe: geometric median clustering with weighted voting for ensemble clustering of cytometry data. Bioinformatics. 39(1). 4 indexed citations
5.
Karagrigoriou, Alex, et al.. (2021). Interdependency Pattern Recognition in Econometrics: A Penalized Regularization Antidote. Econometrics. 9(4). 44–44. 3 indexed citations
6.
Cuff, Simone, et al.. (2021). CytoPy: An autonomous cytometry analysis framework. PLoS Computational Biology. 17(6). e1009071–e1009071. 11 indexed citations
7.
8.
Artemiou, Andreas, et al.. (2020). On the predictive potential of kernel principal components. Electronic Journal of Statistics. 14(1). 1 indexed citations
9.
Artemiou, Andreas, et al.. (2019). Simple Poisson PCA: an algorithm for (sparse) feature extraction with simultaneous dimension determination. Computational Statistics. 35(2). 559–577. 7 indexed citations
10.
Artemiou, Andreas, et al.. (2018). Sparse Generalised Principal Component Analysis. Pattern Recognition. 83. 443–455. 16 indexed citations
11.
Baker, Emily, Karl Michael Schmidt, Matthew Bracher‐Smith, et al.. (2018). Predictive modeling of schizophrenia from genomic data: Comparison of polygenic risk score with kernel support vector machines approach. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 180(1). 80–85. 23 indexed citations
12.
Challoumas, Dimitris & Andreas Artemiou. (2018). Predictors of Attack Performance in High-Level Male Volleyball Players. International Journal of Sports Physiology and Performance. 13(9). 1230–1236. 38 indexed citations
13.
Challoumas, Dimitris, Andreas Artemiou, & G. Dimitrakakis. (2016). Dominant vs. non-dominant shoulder morphology in volleyball players and associations with shoulder pain and spike speed. Journal of Sports Sciences. 35(1). 65–73. 11 indexed citations
14.
Artemiou, Andreas & Yuexiao Dong. (2016). Sufficient dimension reduction via principal L$q$ support vector machine. Electronic Journal of Statistics. 10(1). 12 indexed citations
15.
Artemiou, Andreas, et al.. (2015). Using sliced inverse mean difference for sufficient dimension reduction. Statistics & Probability Letters. 106. 184–190. 3 indexed citations
16.
Artemiou, Andreas & Bing Li. (2013). Predictive power of principal components for single-index model and sufficient dimension reduction. Journal of Multivariate Analysis. 119. 176–184. 10 indexed citations
17.
Srivastava, Soumya K., Andreas Artemiou, & Adrienne Minerick. (2011). Direct current insulator‐based dielectrophoretic characterization of erythrocytes: ABO‐Rh human blood typing. Electrophoresis. 32(18). 2530–2540. 51 indexed citations
18.
Li, Bing, Andreas Artemiou, & Lexin Li. (2011). Principal support vector machines for linear and nonlinear sufficient dimension reduction. The Annals of Statistics. 39(6). 72 indexed citations
19.
Artemiou, Andreas. (2010). Topics on supervised and unsupervised dimension reduction. 1 indexed citations
20.
Artemiou, Andreas & Bing Li. (2009). ON PRINCIPAL COMPONENTS AND REGRESSION: A STATISTICAL EXPLANATION OF A NATURAL PHENOMENON. Statistica Sinica. 19(4). 1557–1565. 15 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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