Ken Tomiyama

497 total citations
54 papers, 321 citations indexed

About

Ken Tomiyama is a scholar working on Artificial Intelligence, Biomedical Engineering and Control and Systems Engineering. According to data from OpenAlex, Ken Tomiyama has authored 54 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Biomedical Engineering and 9 papers in Control and Systems Engineering. Recurrent topics in Ken Tomiyama's work include Robotic Locomotion and Control (10 papers), Educational Robotics and Engineering (7 papers) and Spectroscopy and Laser Applications (5 papers). Ken Tomiyama is often cited by papers focused on Robotic Locomotion and Control (10 papers), Educational Robotics and Engineering (7 papers) and Spectroscopy and Laser Applications (5 papers). Ken Tomiyama collaborates with scholars based in Japan, United States and Norway. Ken Tomiyama's co-authors include Robert J. Rossana, Joseph H. Pierluissi, Richard B. Gomez, W.B. Roush, T.L. CRAVENER, F. X. Kneizys, Dale M. Grimes, Zhidong Wang, Ryosuke Imai and Kazuhiro Kosuge and has published in prestigious journals such as Computers and Electronics in Agriculture, Robotics and Autonomous Systems and Journal of Economic Dynamics and Control.

In The Last Decade

Ken Tomiyama

44 papers receiving 274 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ken Tomiyama Japan 7 73 64 64 32 31 54 321
Xiuyan Liu China 9 120 1.6× 38 0.6× 35 0.5× 9 0.3× 8 0.3× 62 318
Suliadi Firdaus Sufahani Malaysia 10 18 0.2× 106 1.7× 40 0.6× 20 0.6× 8 0.3× 79 415
Simone Borra Italy 5 18 0.2× 21 0.3× 16 0.3× 65 2.0× 8 0.3× 12 291
Yubo Huang China 10 10 0.1× 23 0.4× 30 0.5× 39 1.2× 13 0.4× 40 317
Douglas C. Crocker United States 5 17 0.2× 16 0.3× 18 0.3× 22 0.7× 15 0.5× 8 301
K. D. S. Young United Kingdom 6 25 0.3× 7 0.1× 25 0.4× 41 1.3× 10 0.3× 16 368
Edward F. Wolff United States 9 90 1.2× 24 0.4× 10 0.2× 73 2.3× 7 0.2× 15 535
Renjun Liu China 6 9 0.1× 15 0.2× 69 1.1× 15 0.5× 20 0.6× 31 320
Sihang Qiu China 12 5 0.1× 24 0.4× 28 0.4× 39 1.2× 28 0.9× 27 354
Silvia Bianconcini Italy 9 71 1.0× 8 0.1× 41 0.6× 47 1.5× 10 0.3× 26 320

Countries citing papers authored by Ken Tomiyama

Since Specialization
Citations

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

Fields of papers citing papers by Ken Tomiyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Tomiyama

This figure shows the co-authorship network connecting the top 25 collaborators of Ken Tomiyama. A scholar is included among the top collaborators of Ken Tomiyama 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 Ken Tomiyama. Ken Tomiyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tomiyama, Ken. (2019). Identifying Discourse Boundaries in Group Discussions using Multimodal Features. 1 indexed citations
2.
Tomiyama, Ken, et al.. (2018). Identifying Discourse Boundaries in Group Discussions using a Multimodal Embedding Space.. 1 indexed citations
3.
Imai, Ryosuke, et al.. (2017). Excretion Detection System with Gas Sensor – Proposal and Verification of Algorithm Based on Time-Series Clustering –. Journal of Robotics and Mechatronics. 29(2). 353–363. 5 indexed citations
4.
Tomiyama, Ken, et al.. (2015). Multidisciplinary Educational Framework for Social Implementation of Robotics. Journal of JSEE. 63(1). 1_31–1_36. 1 indexed citations
5.
Tomiyama, Ken, et al.. (2013). Implementation Approach of Affective Interaction for Caregiver Support Robot. Journal of Robotics and Mechatronics. 25(6). 1060–1069. 3 indexed citations
6.
Tomiyama, Ken, et al.. (2012). Attitude Determination by Globally and Asymptotically Stable Estimation of Gyroscope Bias Error with Disturbance Attenuation and Rejection. Journal of Robotics and Mechatronics. 24(2). 389–398. 3 indexed citations
7.
Tomiyama, Ken, et al.. (2011). Hands-on Robotics Instruction Program for Beginners. Journal of Robotics and Mechatronics. 23(5). 799–810. 3 indexed citations
8.
9.
Tomiyama, Ken, et al.. (2005). 2A1-N-028 Head Posture Invariant Detection of Facial Expression(Emotion, Sensitivity, and Embodiment 1,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives). The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2005(0). 139–139. 2 indexed citations
10.
Tomiyama, Ken, et al.. (2004). Design of Controller for Care-Worker Support Robot. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2004(0). 80–80. 1 indexed citations
11.
Takeuchi, Hiroshi, et al.. (2004). Development of a Test Bed Care-Worker Support Robot. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2004(0). 8–9. 2 indexed citations
12.
Tomiyama, Ken, et al.. (2004). Housing Design Assistant for Remodeling Based on AL Approach. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2004(0). 159–160.
13.
Tomiyama, Ken, et al.. (2004). Sensor-Based Biped Gait Generation for Humanoid. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2004(0). 30–31. 1 indexed citations
14.
Tomiyama, Ken, et al.. (2003). A Study on Emotional Influence of Shapes of Care-Worker Support Robot. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2003(0). 46–47. 2 indexed citations
15.
Tomiyama, Ken, et al.. (2003). Design Technique of Virtual KANSEI based on Petri-Net with Learning Capability : Realization of personality. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2003(0). 140–140. 1 indexed citations
16.
Tomiyama, Ken, et al.. (2002). Composition of Virtual Kansei in Narrow and Wide Sense. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2002(0). 64–64. 3 indexed citations
17.
Tomiyama, Ken, et al.. (2002). Construction of Virtual KANSEI using PetriNet with Learning by GA. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2002(0). 64–64. 1 indexed citations
18.
Okada, Hiroyuki, et al.. (2001). 2A1-E3 Real time ZMP Compensation based on Control of Inertia Force for Biped. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2001(0). 45–45. 1 indexed citations
19.
Tomiyama, Ken. (2001). . Nihon Kikai Gakkaishi/Journal of the Japan Society of Mechanical Engineers. 104(994). 622–623. 1 indexed citations
20.
Ota, Jun, et al.. (1994). Automatic Conversion of Mechanical Engineering Drawings to CAD Data.. Journal of the Japan Society for Precision Engineering. 60(4). 524–529. 2 indexed citations

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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