Seunghak Yu

41 total papers · 1.1k total citations
24 papers, 535 citations indexed

About

Seunghak Yu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Seunghak Yu has authored 24 papers receiving a total of 535 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 5 papers in Molecular Biology. Recurrent topics in Seunghak Yu's work include Topic Modeling (12 papers), Multimodal Machine Learning Applications (7 papers) and Natural Language Processing Techniques (5 papers). Seunghak Yu is often cited by papers focused on Topic Modeling (12 papers), Multimodal Machine Learning Applications (7 papers) and Natural Language Processing Techniques (5 papers). Seunghak Yu collaborates with scholars based in South Korea, United States and United Kingdom. Seunghak Yu's co-authors include Giovanni Da San Martino, Preslav Nakov, Alberto Barrón‐Cedeño, Heriberto Cuayáhuitl, Roberto Di Pietro, Idan Schwartz, Tamir Hazan, Stefano Cresci, Alexander G. Schwing and Jihie Kim and has published in prestigious journals such as Bioinformatics, Neurocomputing and Methods.

In The Last Decade

Seunghak Yu

23 papers receiving 506 citations

Author Peers

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

Author Last Decade Papers Cites
Seunghak Yu 405 200 103 84 27 24 535
Minglei Li 289 0.7× 118 0.6× 52 0.5× 113 1.3× 55 2.0× 40 490
Richard Gruss 171 0.4× 169 0.8× 90 0.9× 117 1.4× 14 0.5× 29 503
Chris Bryan 140 0.3× 77 0.4× 246 2.4× 25 0.3× 50 1.9× 38 495
Todor Mihaylov 513 1.3× 104 0.5× 142 1.4× 155 1.8× 10 0.4× 17 614
Shuiqiao Yang 324 0.8× 89 0.4× 61 0.6× 90 1.1× 17 0.6× 26 488
Hao Peng 250 0.6× 45 0.2× 56 0.5× 60 0.7× 36 1.3× 21 531
Mengting Wan 294 0.7× 47 0.2× 66 0.6× 239 2.8× 12 0.4× 34 521
Stephan Raaijmakers 309 0.8× 60 0.3× 74 0.7× 84 1.0× 25 0.9× 44 509
Muhammad Mujahid 251 0.6× 64 0.3× 53 0.5× 54 0.6× 12 0.4× 31 483
Wanjun Zhong 401 1.0× 151 0.8× 63 0.6× 152 1.8× 13 0.5× 36 521

Countries citing papers authored by Seunghak Yu

Since Specialization
Citations

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

Fields of papers citing papers by Seunghak Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seunghak Yu

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