Shushi Namba

Shushi Namba

Associate Professor

Hiroshima University

Biography

Shushi Namba is an Associate Professor of Hiroshima University. My research interests include spontaneous facial expressions, human computing and social cognition.

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Interests

  • Facial Expressions
  • Empathy
  • Computational Modeling

Education

  • PhD in Psychology, 2018

    Hiroshima University

  • M.A. in Psychology, 2016

    Hiroshima University

  • B.A in Psychology, 2014

    Hiroshima University

Skills

R

80%

Statistics

90%

Docker

30%

Music

40%

Accomplish­ments

Machine Learning

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Docker and Kubernetes: The Complete Guide

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Build Responsive Real World Websites with HTML5 and CSS3

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米国AI開発者がゼロから教えるDocker講座 (Docker lecture in Japanese)

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Facial Action Coding System Final Test

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Recent & Upcoming Talks

Recent Publications

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An Android for Emotional Interaction: Spatiotemporal Validation of Its Facial Expressions

Android robots capable of emotional interactions with humans have considerable potential for application to research. While several …
An Android for Emotional Interaction: Spatiotemporal Validation of Its Facial Expressions

Viewpoint Robustness of Automated Facial Action Unit Detection Systems

Automatic facial action detection is important, but no previous studies have evaluated pre-trained models on the accuracy of facial …
Viewpoint Robustness of Automated Facial Action Unit Detection Systems

Fantasy component of interpersonal reactivity is associated with empathic accuracy: findings from behavioral experiments with implications for applied settings

Reading literature contributes to the development of language skills and socioemotional competencies related to empathic responding. …
Fantasy component of interpersonal reactivity is associated with empathic accuracy: findings from behavioral experiments with implications for applied settings

Feedback From Facial Expressions Contribute to Slow Learning Rate in an Iowa Gambling Task

Facial expressions of emotion can convey information about the world and disambiguate elements of the environment, thus providing …
Feedback From Facial Expressions Contribute to Slow Learning Rate in an Iowa Gambling Task

Assessing Automated Facial Action Unit Detection Systems for Analyzing Cross-Domain Facial Expression Databases

In the field of affective computing, achieving accurate automatic detection of facial movements is an important issue, and great …
Assessing Automated Facial Action Unit Detection Systems for Analyzing Cross-Domain Facial Expression Databases

Contact

  • Friday 10:00 to 12:00
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