Shushi Namba

542 total citations
25 papers, 352 citations indexed

About

Shushi Namba is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Social Psychology. According to data from OpenAlex, Shushi Namba has authored 25 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 17 papers in Experimental and Cognitive Psychology and 11 papers in Social Psychology. Recurrent topics in Shushi Namba's work include Face Recognition and Perception (15 papers), Emotion and Mood Recognition (11 papers) and Color perception and design (5 papers). Shushi Namba is often cited by papers focused on Face Recognition and Perception (15 papers), Emotion and Mood Recognition (11 papers) and Color perception and design (5 papers). Shushi Namba collaborates with scholars based in Japan, United Kingdom and Austria. Shushi Namba's co-authors include Makoto Miyatani, Takashi Nakao, Eva G. Krumhuber, Dennis Küster, Wataru Sato, Lina Skora, Manuel G. Calvo, Toshimune Kambara, Hiroshi Matsui and Shin’ya Nishida and has published in prestigious journals such as PLoS ONE, Scientific Reports and Sensors.

In The Last Decade

Shushi Namba

25 papers receiving 340 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shushi Namba Japan 11 226 214 124 61 26 25 352
Chaona Chen United Kingdom 9 123 0.5× 137 0.6× 110 0.9× 41 0.7× 10 0.4× 20 247
Francesca Bacci Italy 8 141 0.6× 233 1.1× 113 0.9× 60 1.0× 15 0.6× 11 326
Susanne Schmidt Germany 4 213 0.9× 287 1.3× 173 1.4× 65 1.1× 8 0.3× 17 417
Lisa N. Jefferies Canada 11 116 0.5× 327 1.5× 90 0.7× 45 0.7× 13 0.5× 22 411
Stefanie Rukavina Germany 6 161 0.7× 178 0.8× 115 0.9× 24 0.4× 12 0.5× 11 327
Verena G. Skuk Germany 12 234 1.0× 250 1.2× 50 0.4× 37 0.6× 58 2.2× 16 439
Tommi Himberg Finland 9 86 0.4× 203 0.9× 142 1.1× 32 0.5× 19 0.7× 14 304
Romi Zäske Germany 13 368 1.6× 420 2.0× 66 0.5× 33 0.5× 10 0.4× 25 553
Rende Shui China 11 92 0.4× 373 1.7× 113 0.9× 32 0.5× 36 1.4× 30 435
Sven‐Thomas Graupner Germany 9 92 0.4× 206 1.0× 85 0.7× 42 0.7× 79 3.0× 16 327

Countries citing papers authored by Shushi Namba

Since Specialization
Citations

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

Fields of papers citing papers by Shushi Namba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shushi Namba

This figure shows the co-authorship network connecting the top 25 collaborators of Shushi Namba. A scholar is included among the top collaborators of Shushi Namba 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 Shushi Namba. Shushi Namba 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.
Nomiya, Hiroki, et al.. (2025). An Artificial Intelligence Model for Sensing Affective Valence and Arousal from Facial Images. Sensors. 25(4). 1188–1188. 1 indexed citations
2.
Namba, Shushi, et al.. (2024). How an Android Expresses “Now Loading…”: Examining the Properties of Thinking Faces. International Journal of Social Robotics. 16(8). 1861–1877. 1 indexed citations
3.
Namba, Shushi, et al.. (2023). Development of the RIKEN database for dynamic facial expressions with multiple angles. Scientific Reports. 13(1). 21785–21785. 2 indexed citations
4.
Namba, Shushi, et al.. (2022). Computational Process of Sharing Emotion: An Authentic Information Perspective. Frontiers in Psychology. 13. 849499–849499. 3 indexed citations
5.
Namba, Shushi, et al.. (2022). The spatio-temporal features of perceived-as-genuine and deliberate expressions. PLoS ONE. 17(7). e0271047–e0271047. 2 indexed citations
6.
Yang, Dongsheng, Wataru Sato, Qianying Liu, et al.. (2022). Optimizing Facial Expressions of an Android Robot Effectively: a Bayesian Optimization Approach. arXiv (Cornell University). 542–549. 4 indexed citations
7.
Sato, Wataru, Shushi Namba, Dongsheng Yang, et al.. (2022). An Android for Emotional Interaction: Spatiotemporal Validation of Its Facial Expressions. Frontiers in Psychology. 12. 800657–800657. 20 indexed citations
8.
Namba, Shushi, et al.. (2021). Distinct temporal features of genuine and deliberate facial expressions of surprise. Scientific Reports. 11(1). 3362–3362. 15 indexed citations
9.
Namba, Shushi. (2021). Feedback From Facial Expressions Contribute to Slow Learning Rate in an Iowa Gambling Task. Frontiers in Psychology. 12. 684249–684249. 3 indexed citations
10.
11.
Namba, Shushi, et al.. (2021). Assessing Automated Facial Action Unit Detection Systems for Analyzing Cross-Domain Facial Expression Databases. Sensors. 21(12). 4222–4222. 33 indexed citations
12.
Liu, Xinyi, et al.. (2021). Sound-Symbolic Semantics of Written Japanese Vowels in a Paper-Based Survey Study. Frontiers in Communication. 6. 8 indexed citations
13.
14.
Perusquía-Hernández, Monica, et al.. (2021). Smile Action Unit detection from distal wearable Electromyography and Computer Vision. 1–8. 14 indexed citations
15.
Namba, Shushi, Wataru Sato, & Sakiko Yoshikawa. (2021). Viewpoint Robustness of Automated Facial Action Unit Detection Systems. Applied Sciences. 11(23). 11171–11171. 11 indexed citations
16.
Krumhuber, Eva G., Dennis Küster, Shushi Namba, & Lina Skora. (2020). Human and machine validation of 14 databases of dynamic facial expressions. Behavior Research Methods. 53(2). 686–701. 45 indexed citations
17.
Krumhuber, Eva G., et al.. (2019). Emotion recognition from posed and spontaneous dynamic expressions: Human observers versus machine analysis.. Emotion. 21(2). 447–451. 47 indexed citations
18.
Namba, Shushi, et al.. (2018). Dynamic Displays Enhance the Ability to Discriminate Genuine and Posed Facial Expressions of Emotion. Frontiers in Psychology. 9. 672–672. 21 indexed citations
19.
Namba, Shushi, et al.. (2017). Spontaneous Facial Actions Map onto Emotional Experiences in a Non-social Context: Toward a Component-Based Approach. Frontiers in Psychology. 8. 633–633. 12 indexed citations
20.
Namba, Shushi, et al.. (2017). Spontaneous Facial Expressions Reveal New Action Units for the Sad Experiences. Journal of Nonverbal Behavior. 41(3). 203–220. 16 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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