Kuniaki Yajima
- Human-Computer Interaction top 2%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Education
- Co-authors
- Nobuyuki OgawaHideyuki KanematsuToshirō KobayashiTatsuya ShiraiDana M. BarryKatsuko T. NakahiraMasashi KawaguchiMichiko Yoshitake
- Topics
- Educational Robotics and Engineering (12 papers)Higher Education Learning Practices (7 papers)Augmented Reality Applications (6 papers)
- Journals
- ACS Applied Materials & InterfacesIEICE Transactions on Information and SystemsInternational Journal of Engineering Pedagogy (iJEP)
- Partner nations
- JapanUnited StatesThailand
In The Last Decade
Kuniaki Yajima
44 papers receiving 373 citations
Peers
Comparison fields: 5 of 79
- Human-Computer Interaction 158
- Information Systems 124
- Computer Vision and Pattern Recognition 63
- Artificial Intelligence 59
- Education 53
Countries citing papers authored by Kuniaki Yajima
This map shows the geographic impact of Kuniaki Yajima'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 Kuniaki Yajima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuniaki Yajima more than expected).
Fields of papers citing papers by Kuniaki Yajima
This network shows the impact of papers produced by Kuniaki Yajima. 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 Kuniaki Yajima. The network helps show where Kuniaki Yajima may publish in the future.
Co-authorship network of co-authors of Kuniaki Yajima
This figure shows the co-authorship network connecting the top 25 collaborators of Kuniaki Yajima. A scholar is included among the top collaborators of Kuniaki Yajima 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 Kuniaki Yajima. Kuniaki Yajima is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 152 | |
| 10 | 2 | |
| 11 | 3 | |
| 12 | 6 | |
| 13 | 2 | |
| 14 | 6 | |
| 15 | 1 | |
| 16 | SKIN TEMPERETURE AS A POSSIBLE INDICATOR OF STUDENT’S INVOLVEMENT IN E-LEARNING SESSIONS | 3 |
| 17 | 2 | |
| 18 | 7 | |
| 19 | 18 | |
| 20 | Evaluating the attitude of a student in e-learning sessions by physiological signals | 1 |
About Kuniaki Yajima
Kuniaki Yajima is a scholar working on Human-Computer Interaction, Computer Science Applications and Health Information Management, having authored 51 papers that have together received 398 indexed citations. Recurring topics across this work include Educational Robotics and Engineering (12 papers), Higher Education Learning Practices (7 papers) and Augmented Reality Applications (6 papers). The work is most often cited by research in Human-Computer Interaction (158 citations), Information Systems (124 citations) and Computer Science Applications (24 citations). Kuniaki Yajima has collaborated with scholars based in Japan, United States and Thailand. Frequent co-authors include Nobuyuki Ogawa, Hideyuki Kanematsu, Toshirō Kobayashi, Tatsuya Shirai, Dana M. Barry, Katsuko T. Nakahira, Masashi Kawaguchi, Michiko Yoshitake, Yoshimi Fukumura and Jun Sato. Their work appears in journals such as ACS Applied Materials & Interfaces, IEICE Transactions on Information and Systems and International Journal of Engineering Pedagogy (iJEP).
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.