Here at Dolylab (Prof. Sugaya Midori: Doly), our research focuses on emotion classification research, its innovative application, or system development, and so on.
Research regarding emotion classification will require the following additional knowledge, on top of basic computer science subjects.
- Measurement of biological information, analysis of the measured data (from heart rate sensor, brain wave measurement), signal processing and analysis
- Statistical analysis
- Machine learning
- Application (Robot, Embedded system, Computer Graphics and so on)
The IGP students will not only systematically learn this knowledge, but also support laboratory students in their research. We strongly wish to create the most suitable education method for IGP students by combining the IGP curriculum and the lab curriculum.
Faculty Members
- Midori Sugaya [Profile]
- Peeraya Sripian (Gift) [Profile]
- Tipporn Laohakangvalvit (Tip) [Profile]
- Adilin Anuardi [Profile]
Student Members (Fall, 2020)
| Name | Research Topics |
|---|---|
| Sayyedjavad Ziaratnia (Javad) | pNN50 Estimation From Facial Videos Using a Spatiotemporal Representation With Convolutional Neural Networks |
| Kiruthika Raja (Kiru) | Study of Suitable Empathy Synchronization Method (Biological Signal vs Facial Expression) for Robot Facial Expression |
| He Haochen (Hanser) | Study on emotional changes by red and green colors while listening to Waltz music |
Lab Curriculum
In addition to general interdisciplinary courses, we actively promote research-based learning from the first year, in which the students get a chance to learn how to conduct research and try to conduct their own research and experiment based on their interests. The students work closely with faculty members and Japanese and international senior students in the laboratory to develop their research skill and experience through hands-on guidance and constant discussion.
In addition, we provide exclusive courses throughout the four years in our laboratory so that the students can make the most out of their abilities on the research. The courses focus on developing the skills in several branches of Computer Science through basic knowledge and applications. The overall four-year curriculum of our laboratory is as follows:
| Year | Semester | Research Survey and Discussion | Research Practice and Exercise |
|---|---|---|---|
| 1st | 1st (Fall) | - Affective computing (Basics) | - Biological signal processing: Experiment and data analysis (Basics) - IoT device development (Basics) |
| 2nd (Spring) | - Machine learning (Basics) | - Data structure and algorithm (Basics) - IoT device development with Robots (Advanced) |
|
| 2nd | 1st (Fall) | - Affective computing (Advanced) | - Biological signal processing: Experiment and data analysis (Advanced) - Digital Media Processing (Basics) - Tentative - Programming Contest |
| 2nd (Spring) | - Machine learning (Advanced) - Research topics of own interest | - Data structure and algorithm (Advanced) | |
| 3rd | 1st (Fall) | - Recent research papers | - Machine learning exercise - System programming - Tentative |
| 2nd (Spring) | - Recent research papers | - Conduct own senior research | |
| 4th | 1st (Fall) | - Recent research papers | - Conduct own senior research |
| 2nd (Spring) | - Recent research papers | - Conduct own senior research |