Tomoyuki Uchida

188 total papers · 1.5k total citations
78 papers, 346 citations indexed

About

Tomoyuki Uchida is a scholar working on Artificial Intelligence, Hematology and Molecular Biology. According to data from OpenAlex, Tomoyuki Uchida has authored 78 papers receiving a total of 346 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 22 papers in Hematology and 15 papers in Molecular Biology. Recurrent topics in Tomoyuki Uchida's work include Algorithms and Data Compression (17 papers), Evolutionary Algorithms and Applications (11 papers) and Machine Learning and Algorithms (10 papers). Tomoyuki Uchida is often cited by papers focused on Algorithms and Data Compression (17 papers), Evolutionary Algorithms and Applications (11 papers) and Machine Learning and Algorithms (10 papers). Tomoyuki Uchida collaborates with scholars based in Japan, United States and United Kingdom. Tomoyuki Uchida's co-authors include Yusuke Suzuki, Takayoshi Shoudai, Tetsuhiro Miyahara, Masao Hagihara, Fumio Nakahara, Toshio Kitamura, Jiro Kitaura, Narandalai Danshiitsoodol, Masafumi Noda and Keishi Kanno and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and The Journal of Immunology.

In The Last Decade

Tomoyuki Uchida

62 papers receiving 342 citations

Author Peers

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

Author						Papers	Cites
Tomoyuki Uchida	115	72	63	53	40	78	346
Murat Albayrak	35 0.3×	95 1.3×	93 1.5×	30 0.6×	48 1.2×	86	367
Ruba Y. Taha	97 0.8×	16 0.2×	42 0.7×	32 0.6×	31 0.8×	39	325
Halima El Omri	135 1.2×	17 0.2×	87 1.4×	33 0.6×	20 0.5×	47	351
Jun Ma	132 1.1×	12 0.2×	73 1.2×	30 0.6×	22 0.6×	47	401
Yiyan Zhang	115 1.0×	28 0.4×	11 0.2×	48 0.9×	14 0.3×	37	389
Ke Shen	93 0.8×	15 0.2×	41 0.7×	30 0.6×	23 0.6×	53	304
Minju Kim	147 1.3×	9 0.1×	48 0.8×	34 0.6×	26 0.7×	32	363
Wenjun Tang	65 0.6×	38 0.5×	25 0.4×	13 0.2×	30 0.8×	29	349
Ling Shen	262 2.3×	15 0.2×	28 0.4×	26 0.5×	40 1.0×	29	401
Peng‐Chan Lin	132 1.1×	21 0.3×	28 0.4×	22 0.4×	12 0.3×	50	374

Countries citing papers authored by Tomoyuki Uchida

Since Specialization

Citations

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

Fields of papers citing papers by Tomoyuki Uchida

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoyuki Uchida

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