Kyriakos Efthymiadis

751 total citations
20 papers, 268 citations indexed

About

Kyriakos Efthymiadis is a scholar working on Artificial Intelligence, Spectroscopy and Analytical Chemistry. According to data from OpenAlex, Kyriakos Efthymiadis has authored 20 papers receiving a total of 268 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 4 papers in Spectroscopy and 4 papers in Analytical Chemistry. Recurrent topics in Kyriakos Efthymiadis's work include Reinforcement Learning in Robotics (7 papers), Analytical Chemistry and Chromatography (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Kyriakos Efthymiadis is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Analytical Chemistry and Chromatography (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Kyriakos Efthymiadis collaborates with scholars based in Belgium, United Kingdom and Netherlands. Kyriakos Efthymiadis's co-authors include Gert Desmet, Alexander Kensert, Deirdre Cabooter, Daniel Kudenko⋆, Peter Van den Broeck, Ann Nowé, Robbin Bouwmeester, Ant Crook, Liana E. Kafetzopoulou and Emma Aarons and has published in prestigious journals such as Analytical Chemistry, Journal of Chromatography A and IEEE Access.

In The Last Decade

Kyriakos Efthymiadis

17 papers receiving 259 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyriakos Efthymiadis Belgium 9 84 62 57 55 46 20 268
Lucas C. Ribas Brazil 10 71 0.8× 29 0.5× 7 0.1× 56 1.0× 7 0.2× 26 283
Aditya Goel India 9 38 0.5× 37 0.6× 4 0.1× 22 0.4× 27 0.6× 59 353
Leonardo Scabini Brazil 8 64 0.8× 23 0.4× 7 0.1× 50 0.9× 8 0.2× 17 238
Jatinder Manhas India 12 50 0.6× 186 3.0× 3 0.1× 40 0.7× 22 0.5× 32 475
Tim Andersen United States 12 290 3.5× 90 1.5× 5 0.1× 41 0.7× 4 0.1× 48 519
Wei Jin China 15 253 3.0× 92 1.5× 58 1.0× 440 8.0× 68 1.5× 45 737
Xiaoping Min China 10 218 2.6× 28 0.5× 4 0.1× 104 1.9× 4 0.1× 34 336
Muhammad Roman Pakistan 13 47 0.6× 79 1.3× 4 0.1× 70 1.3× 12 0.3× 33 453
Zhen Guo China 10 88 1.0× 21 0.3× 4 0.1× 29 0.5× 14 0.3× 33 423

Countries citing papers authored by Kyriakos Efthymiadis

Since Specialization
Citations

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

Fields of papers citing papers by Kyriakos Efthymiadis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kyriakos Efthymiadis

This figure shows the co-authorship network connecting the top 25 collaborators of Kyriakos Efthymiadis. A scholar is included among the top collaborators of Kyriakos Efthymiadis 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 Kyriakos Efthymiadis. Kyriakos Efthymiadis 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.
2.
Efthymiadis, Kyriakos, et al.. (2024). Fusion of multi-temporal PlanetScope data and very high-resolution aerial imagery for urban tree species mapping. Urban forestry & urban greening. 99. 128410–128410. 7 indexed citations
3.
Efthymiadis, Kyriakos, et al.. (2023). Tree species mapping in the Brussels Capital Region using deep learning and data fusion. 1–4. 1 indexed citations
4.
Kensert, Alexander, et al.. (2022). Convolutional neural network for automated peak detection in reversed-phase liquid chromatography. Journal of Chromatography A. 1672. 463005–463005. 19 indexed citations
5.
Efthymiadis, Kyriakos, et al.. (2022). A framework for flexibly guiding learning agents. Neural Computing and Applications. 37(19). 13101–13117.
6.
Efthymiadis, Kyriakos, Albert De Beir, Uroš Marušič, et al.. (2022). Deep learning for biosignal control: insights from basic to real-time methods with recommendations. Journal of Neural Engineering. 19(1). 11003–11003. 19 indexed citations
7.
Kensert, Alexander, et al.. (2021). Deep Q-learning for the selection of optimal isocratic scouting runs in liquid chromatography. Journal of Chromatography A. 1638. 461900–461900. 18 indexed citations
8.
Kensert, Alexander, Robbin Bouwmeester, Kyriakos Efthymiadis, et al.. (2021). Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data. Analytical Chemistry. 93(47). 15633–15641. 34 indexed citations
9.
Kensert, Alexander, et al.. (2021). Deep convolutional autoencoder for the simultaneous removal of baseline noise and baseline drift in chromatograms. Journal of Chromatography A. 1646. 462093–462093. 28 indexed citations
10.
Efthymiadis, Kyriakos, et al.. (2020). Application of evolutionary algorithms to optimise one- and two-dimensional gradient chromatographic separations. Journal of Chromatography A. 1628. 461435–461435. 16 indexed citations
11.
Efthymiadis, Kyriakos, et al.. (2019). GUARDIAML: Machine Learning-Assisted Dynamic Information Flow Control. VUBIR (Vrije Universiteit Brussel). 624–628.
12.
Rădulescu, Roxana, et al.. (2019). Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands. VUBIR (Vrije Universiteit Brussel). 2 indexed citations
13.
Efthymiadis, Kyriakos, et al.. (2019). SWAT: Seamless Web Authentication Technology. VUBIR (Vrije Universiteit Brussel). 1579–1589. 4 indexed citations
14.
Efthymiadis, Kyriakos, Tom Lenaerts, Ann Nowé, et al.. (2019). Distilling Deep Reinforcement Learning Policies in Soft Decision Trees. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 1–6. 26 indexed citations
15.
Kafetzopoulou, Liana E., Kyriakos Efthymiadis, Kuiama Lewandowski, et al.. (2018). Assessment of metagenomic Nanopore and Illumina sequencing for recovering whole genome sequences of chikungunya and dengue viruses directly from clinical samples. Eurosurveillance. 23(50). 63 indexed citations
16.
Efthymiadis, Kyriakos, Sam Devlin, & Daniel Kudenko⋆. (2016). Overcoming incorrect knowledge in plan-based reward shaping. The Knowledge Engineering Review. 31(1). 31–43. 5 indexed citations
17.
Efthymiadis, Kyriakos, Sam Devlin, & Daniel Kudenko⋆. (2014). Knowledge revision for reinforcement learning with abstract MDPs. Adaptive Agents and Multi-Agents Systems. 763–770. 4 indexed citations
18.
Efthymiadis, Kyriakos & Daniel Kudenko⋆. (2014). A comparison of plan-based and abstract MDP reward shaping. Connection Science. 26(1). 85–99. 2 indexed citations
19.
Efthymiadis, Kyriakos, Sam Devlin, & Daniel Kudenko⋆. (2013). Overcoming erroneous domain knowledge in plan-based reward shaping. Adaptive Agents and Multi-Agents Systems. 1245–1246. 2 indexed citations
20.
Efthymiadis, Kyriakos & Daniel Kudenko⋆. (2013). Using plan-based reward shaping to learn strategies in StarCraft: Broodwar. 1–8. 18 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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