Toshiyuki Maeda

256 total papers · 1.3k total citations
122 papers, 843 citations indexed

About

Toshiyuki Maeda is a scholar working on Pulmonary and Respiratory Medicine, Hardware and Architecture and Artificial Intelligence. According to data from OpenAlex, Toshiyuki Maeda has authored 122 papers receiving a total of 843 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Pulmonary and Respiratory Medicine, 20 papers in Hardware and Architecture and 20 papers in Artificial Intelligence. Recurrent topics in Toshiyuki Maeda's work include Parallel Computing and Optimization Techniques (11 papers), Aortic aneurysm repair treatments (11 papers) and Aortic Disease and Treatment Approaches (11 papers). Toshiyuki Maeda is often cited by papers focused on Parallel Computing and Optimization Techniques (11 papers), Aortic aneurysm repair treatments (11 papers) and Aortic Disease and Treatment Approaches (11 papers). Toshiyuki Maeda collaborates with scholars based in Japan, United Kingdom and China. Toshiyuki Maeda's co-authors include Shuji Hamada, Seiji Kajihara, Yasuo Satô, Maho Nakata, Masatomo Hashimoto, Tomomi Shimazaki, Nobuyoshi Kawaharada, Tetsuya Higami, Yoshitaka Sasaki and Tatsuya Yoshino and has published in prestigious journals such as The Journal of Physical Chemistry, Carbon and Catalysis Today.

In The Last Decade

Toshiyuki Maeda

108 papers receiving 798 citations

Author Peers

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

Author						Papers	Cites
Toshiyuki Maeda	248	232	114	89	79	122	843
Kenji Sawada	134 0.5×	28 0.1×	235 2.1×	56 0.6×	53 0.7×	137	808
Bhaskar Ghosh	127 0.5×	56 0.2×	32 0.3×	160 1.8×	36 0.5×	85	999
Hung‐Yu Wang	407 1.6×	34 0.1×	94 0.8×	43 0.5×	34 0.4×	81	865
Xi Wu	187 0.8×	78 0.3×	204 1.8×	113 1.3×	11 0.1×	59	955
Bingbing Li	110 0.4×	54 0.2×	18 0.2×	223 2.5×	69 0.9×	103	1.0k
Raj Kamal	89 0.4×	29 0.1×	73 0.6×	196 2.2×	57 0.7×	103	1.0k
Nan Li	123 0.5×	35 0.2×	57 0.5×	303 3.4×	33 0.4×	91	1000
Qingxian Wang	68 0.3×	40 0.2×	49 0.4×	223 2.5×	114 1.4×	135	900
Xi Li	119 0.5×	27 0.1×	263 2.3×	15 0.2×	46 0.6×	47	767
Jiaxin Jiang	96 0.4×	14 0.1×	80 0.7×	136 1.5×	55 0.7×	84	748

Countries citing papers authored by Toshiyuki Maeda

Since Specialization

Citations

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

Fields of papers citing papers by Toshiyuki Maeda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Toshiyuki Maeda

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