Vladimir Shin

138 total papers · 699 total citations
79 papers, 495 citations indexed

About

Vladimir Shin is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Networks and Communications. According to data from OpenAlex, Vladimir Shin has authored 79 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 38 papers in Control and Systems Engineering and 23 papers in Computer Networks and Communications. Recurrent topics in Vladimir Shin's work include Target Tracking and Data Fusion in Sensor Networks (54 papers), Fault Detection and Control Systems (30 papers) and Distributed Sensor Networks and Detection Algorithms (23 papers). Vladimir Shin is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (54 papers), Fault Detection and Control Systems (30 papers) and Distributed Sensor Networks and Detection Algorithms (23 papers). Vladimir Shin collaborates with scholars based in South Korea, Russia and United States. Vladimir Shin's co-authors include Du Yong Kim, Moongu Jeon, Tae‐Sun Choi, Georgy Shevlyakov, Ju Hong Yoon, Jong Keun Seon, Kiseon Kim, Yeon Soo Lee, Yoon Hyuk Kim and Eun Kyoo Song and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Industrial Electronics and IEEE Transactions on Signal Processing.

In The Last Decade

Vladimir Shin

73 papers receiving 470 citations

Author Peers

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

Author						Papers	Cites
Vladimir Shin	256	145	125	100	76	79	495
Shan Gao	137 0.5×	54 0.4×	137 1.1×	69 0.7×	58 0.8×	68	526
Yanjie Li	108 0.4×	81 0.6×	46 0.4×	91 0.9×	84 1.1×	62	540
Takashi Yokota	47 0.2×	74 0.5×	126 1.0×	30 0.3×	97 1.3×	106	541
Kathleen Kramer	162 0.6×	108 0.7×	35 0.3×	190 1.9×	78 1.0×	84	413
Xianling Li	69 0.3×	253 1.7×	68 0.5×	50 0.5×	57 0.8×	46	549
Christoffer Heckman	108 0.4×	64 0.4×	81 0.6×	242 2.4×	78 1.0×	42	500
Yi Gong	67 0.3×	29 0.2×	97 0.8×	101 1.0×	238 3.1×	50	437
Wenli Shang	113 0.4×	90 0.6×	134 1.1×	35 0.3×	126 1.7×	73	544
Leena Vachhani	48 0.2×	132 0.9×	68 0.5×	101 1.0×	61 0.8×	57	417
Qi Song	160 0.6×	82 0.6×	18 0.1×	141 1.4×	58 0.8×	35	510

Countries citing papers authored by Vladimir Shin

Since Specialization

Citations

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

Fields of papers citing papers by Vladimir Shin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vladimir Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Vladimir Shin. A scholar is included among the top collaborators of Vladimir Shin 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 Vladimir Shin. Vladimir Shin 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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