Ioannis Vlachos

1.9k total citations · 1 hit paper
47 papers, 1.4k citations indexed

About

Ioannis Vlachos is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ioannis Vlachos has authored 47 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cognitive Neuroscience, 10 papers in Artificial Intelligence and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ioannis Vlachos's work include EEG and Brain-Computer Interfaces (16 papers), Neural dynamics and brain function (12 papers) and Functional Brain Connectivity Studies (7 papers). Ioannis Vlachos is often cited by papers focused on EEG and Brain-Computer Interfaces (16 papers), Neural dynamics and brain function (12 papers) and Functional Brain Connectivity Studies (7 papers). Ioannis Vlachos collaborates with scholars based in Greece, United States and Czechia. Ioannis Vlachos's co-authors include George D. Sergiadis, Dimitris Kugiumtzis, Leonidas Iasemidis, Balu Krishnan, Konstantinos Tsakalis, David M. Treiman, Pavan Turaga, Edward Glasscock, Gerhard M. Friehs and Joshua A. Adkinson and has published in prestigious journals such as Nature Communications, PLoS ONE and Neurology.

In The Last Decade

Ioannis Vlachos

43 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Intuitionistic fuzzy information – Applications to pattern recognition

2006 607 citations Ioannis Vlachos, George D. Sergiadis Pattern Recognition Letters profile →

Peers

Ioannis Vlachos

MSOR

AI

CN

SP

CTM

Jean‐Claude Fort France

Richard Dearden United Kingdom

Youyong Kong China

Michael Eichler Netherlands

Petros Xanthopoulos United States

Maurizio Filippone United Kingdom

Bor‐Chen Kuo Taiwan

Jiqing Qiu China

Ana Carolina Lorena Brazil

Abdoljalil Addeh Iran

Jean‐Claude Fort France

Ioannis Vlachos

135 ×0.2

MSOR

505 ×1.3

AI

222 ×0.7

CN

101 ×0.4

SP

69 ×0.3

CTM

Citations per year, relative to Ioannis Vlachos Ioannis Vlachos (= 1×) peers Jean‐Claude Fort

Countries citing papers authored by Ioannis Vlachos

Since Specialization

Citations

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

Fields of papers citing papers by Ioannis Vlachos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ioannis Vlachos

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

All Works

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20 of 20 papers shown

1.

Vlachos, Ioannis, Dimitris Kugiumtzis, & Milan Paluš. (2024). Causality from phases of high-dimensional nonlinear systems. Information Sciences. 697. 121761–121761.

2.

Cruz, Janir Nuno da, A. Sobolewski, Markus Fuchs, et al.. (2024). Feasibility, Safety, and Performance of Full-Head Subscalp EEG Using Minimally Invasive Electrode Implantation. Neurology. 102(12). e209428–e209428. 2 indexed citations

3.

Vlachos, Ioannis, et al.. (2023). Auditory Fine-Tuned Suppressor of TMS-Clicks (TMS-Click AFTS): A Novel, Perceptually Driven/Tuned Approach for the Reduction in AEP Artifacts in TMS-EEG Studies. Applied Sciences. 13(2). 1047–1047.

4.

Vlachos, Ioannis, et al.. (2023). Detecting Nonlinear Interactions in Complex Systems: Application in Financial Markets. Entropy. 25(2). 370–370. 6 indexed citations

5.

Vlachos, Ioannis, Ioannis Markakis, Theodoros Samaras, et al.. (2022). The Relation between Induced Electric Field and TMS-Evoked Potentials: A Deep TMS-EEG Study. Applied Sciences. 12(15). 7437–7437. 2 indexed citations

6.

Chaudhary, Ujwal, Ioannis Vlachos, Jonas B. Zimmermann, et al.. (2022). Spelling interface using intracortical signals in a completely locked-in patient enabled via auditory neurofeedback training. Nature Communications. 13(1). 1236–1236. 75 indexed citations

7.

Vlachos, Ioannis, et al.. (2021). TMS-induced brain connectivity modulation in Genetic Generalized Epilepsy. Clinical Neurophysiology. 133. 83–93. 9 indexed citations

8.

Adkinson, Joshua A., et al.. (2018). Multivariate Matching Pursuit Decomposition and Normalized Gabor Entropy for Quantification of Preictal Trends in Epilepsy. Entropy. 20(6). 419–419. 5 indexed citations

9.

Adkinson, Joshua A., et al.. (2018). Connectivity and Centrality Characteristics of the Epileptogenic Focus Using Directed Network Analysis. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27(1). 22–30. 18 indexed citations

10.

Vlachos, Ioannis, et al.. (2016). Classification of Pre-ictal and Interictal Periods Based on EEG Frequency Features in Epilepsy. 25. 9–10. 3 indexed citations

11.

Vlachos, Ioannis, et al.. (2015). Dynamical Regularity for Action Analysis. 67.1–67.12. 23 indexed citations

12.

Krishnan, Balu, Ioannis Vlachos, John C. Mosher, et al.. (2014). Epileptic focus localization based on resting state interictal MEG recordings is feasible irrespective of the presence or absence of spikes. Clinical Neurophysiology. 126(4). 667–674. 29 indexed citations

13.

Krishnan, Balu, et al.. (2014). A Novel Spatiotemporal Analysis of Peri-Ictal Spiking to Probe the Relation of Spikes and Seizures in Epilepsy. Annals of Biomedical Engineering. 42(8). 1606–1617. 18 indexed citations

14.

Krishnan, Balu, et al.. (2011). Resetting of brain dynamics: epileptic versus psychogenic nonepileptic seizures. Epilepsy & Behavior. 22. S74–S81. 13 indexed citations

15.

Vlachos, Ioannis & Dimitris Kugiumtzis. (2010). Nonuniform state-space reconstruction and coupling detection. Physical Review E. 82(1). 16207–16207. 141 indexed citations

16.

Vlachos, Ioannis & Dimitris Kugiumtzis. (2009). State Space Reconstruction from Multiple Time Series. 378–387. 26 indexed citations

17.

Vlachos, Ioannis & George D. Sergiadis. (2006). Intuitionistic fuzzy information – Applications to pattern recognition. Pattern Recognition Letters. 28(2). 197–206. 607 indexed citations breakdown →

18.

Vlachos, Ioannis & George D. Sergiadis. (2006). On the Entropy of Intuitionistic Fuzzy Events. 2. 153–158. 2 indexed citations

19.

Vlachos, Ioannis & George D. Sergiadis. (2003). Edge Detection By Fusion Using Local Information of Edges. 한국지능시스템학회 국제학술대회 발표논문집. 403–406. 3 indexed citations

20.

Vlachos, Ioannis & George D. Sergiadis. (2003). Quality Measures for Image Comparison Based on Correlation of Fuzzy Sets. 한국지능시스템학회 국제학술대회 발표논문집. 563–566. 4 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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