D. Kazakos

114 total papers · 724 total citations
67 papers, 491 citations indexed

About

D. Kazakos is a scholar working on Computer Networks and Communications, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, D. Kazakos has authored 67 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Networks and Communications, 27 papers in Artificial Intelligence and 16 papers in Statistics and Probability. Recurrent topics in D. Kazakos's work include Distributed Sensor Networks and Detection Algorithms (23 papers), Target Tracking and Data Fusion in Sensor Networks (20 papers) and Advanced Statistical Process Monitoring (12 papers). D. Kazakos is often cited by papers focused on Distributed Sensor Networks and Detection Algorithms (23 papers), Target Tracking and Data Fusion in Sensor Networks (20 papers) and Advanced Statistical Process Monitoring (12 papers). D. Kazakos collaborates with scholars based in United States, Greece and Taiwan. D. Kazakos's co-authors include P. Papantoni‐Kazakos, Lazaros Merakos, Ioannis Stavrakakis, Dimitris A. Pados, H. Deliç, Theodοre Zahariadis, Stella N. Batalama, K.W. Halford, L. Davisson and Wei Li and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Information Theory and IEEE Transactions on Signal Processing.

In The Last Decade

D. Kazakos

60 papers receiving 454 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
D. Kazakos	289	191	156	78	69	67	491
M. Kraetzl	172 0.6×	139 0.7×	66 0.4×	45 0.6×	27 0.4×	39	448
Dragana Bajović	360 1.2×	200 1.0×	176 1.1×	58 0.7×	17 0.2×	53	516
Shaofeng Zou	169 0.6×	253 1.3×	104 0.7×	85 1.1×	114 1.7×	69	530
J.L. Hammond	266 0.9×	44 0.2×	165 1.1×	26 0.3×	38 0.6×	35	467
Aurélien Garivier	104 0.4×	279 1.5×	63 0.4×	34 0.4×	50 0.7×	26	418
András Antos	92 0.3×	350 1.8×	51 0.3×	54 0.7×	74 1.1×	20	509
Sukhamay Kundu	113 0.4×	122 0.6×	71 0.5×	32 0.4×	38 0.6×	48	551
Ryohei Fujimaki	97 0.3×	309 1.6×	17 0.1×	64 0.8×	40 0.6×	40	503
Felisa J. Vázquez-Abad	109 0.4×	58 0.3×	60 0.4×	46 0.6×	94 1.4×	56	446
Mohammad Naghshvar	333 1.2×	168 0.9×	123 0.8×	71 0.9×	23 0.3×	24	453

Countries citing papers authored by D. Kazakos

Since Specialization

Citations

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

Fields of papers citing papers by D. Kazakos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Kazakos

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

All Works

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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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