Maomi Ueno

57 papers and 279 indexed citations i.

About

Maomi Ueno is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Maomi Ueno has authored 57 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 18 papers in Information Systems and 11 papers in Management Science and Operations Research. Recurrent topics in Maomi Ueno’s work include Bayesian Modeling and Causal Inference (13 papers), Educational Technology and Assessment (11 papers) and Intelligent Tutoring Systems and Adaptive Learning (9 papers). Maomi Ueno is often cited by papers focused on Bayesian Modeling and Causal Inference (13 papers), Educational Technology and Assessment (11 papers) and Intelligent Tutoring Systems and Adaptive Learning (9 papers). Maomi Ueno collaborates with scholars based in Japan, Thailand and The Netherlands. Maomi Ueno's co-authors include Masaki Uto, Toshio Okamoto, Joe Suzuki, Kazuo Shigemasu, Wim J. van der Linden, Minoru Nakayama, Takahiro Yamazaki, Yasuhiko Morimoto, Takenori Ogawa and Yoshio Mino and has published in prestigious journals such as PLoS ONE, IEEE Access and Educational Technology Research and Development.

In The Last Decade

Co-authorship network of co-authors of Maomi Ueno i

Fields of papers citing papers by Maomi Ueno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maomi Ueno

Since Specialization
Citations

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

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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2025