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
Student Members
B2
| Name | Research Topics |
|---|---|
| Sayyedjavad Ziaratnia (Javad) | Remote Assessment of Depression Using A Multimodal Deep Learning A CNN-LSTM Approach for pNN50 Estimation |
| Kiruthika Raja (Kiru) | Towards the Development of a Platform for Real-Time Health Monitoring System |
| He Haochen (Hanser) | Study of changes in biological signals according to differences in brightness of red color |
B1
| Name | |
|---|---|
| Chen Le Gao (Henry) | Toward an improvement of performance for IoT-based platform in heterogeneous computing and edge computing |
| Aarif Suksai (Reef) | Study on Emotional Effect of Different Genres of Music on Biological Signal in Driving Simulation |
| Udit Bhakta Pradhan (Udit) | The Effect of Different Genres of Music on the Qualitative and Quantitative Experience on Physical Exercise |
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) | - Own research - Lab rotation 1,2 & Progress | |
| 2nd (Spring) | - Own research - Lab rotation 3,4 & Progress | ||
| 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 |