About Distributed and Collaborative Systems Laboratory
Our laboratory conducts research on information technologies that connect people, information, and the physical world. Based on the concepts of Distributed Systems and Collaboration, our work is driven by three key themes: Networking, Intelligence, and Real-World Support.
We aim to create new value and experiences by enabling information sharing through networks, understanding and utilizing data with AI, and supporting human activities and daily life in the real world. Through the integration of these technologies, we seek to bridge the gap between cyberspace and the physical world.
Our research covers a wide range of topics, including information services such as search, meetings, and learning support; AI technologies for recommendation, recognition, and content generation; as well as systems that support physical activity, health, and human behavior. Starting from real-world challenges, we place strong emphasis on developing practical systems that make a meaningful impact on society.
In all of our activities, we embrace the principles of Challenge, Global, and Fun. We encourage students to take on new technologies and unexplored problems, develop a global perspective, and enjoy the process of research and innovation.
Research Areas
Network Services
Overview
We conduct research on systems that connect people and information through networks and support information search, sharing, and collaboration. Our goal is to enable smooth communication and efficient information exchange in activities involving multiple users, such as online meetings, information retrieval, and travel planning.
Research Topics
- Meeting and communication support
- Academic paper and product search support
- Travel planning and information sharing
- Learning and collaborative work support
Intelligent Systems
Overview
We conduct research on intelligent systems that support human cognitive activities through artificial intelligence technologies. In particular, we leverage large language models and deep learning techniques to develop recommendation, recognition, language understanding, and content generation systems that can extract meaning from data and provide appropriate information and decision support.
Research Topics
- Recommender systems
- Image recognition and activity recognition
- Natural language processing (generation and transformation)
- Multimodal analysis
Real-World Computing
Overview
We conduct research on systems that support human behavior, daily life, and experiences by acquiring and analyzing real-world data from sensors, wearable devices, and other sensing technologies. Our goal is to provide personalized feedback and behavioral support based on users’ physical and mental states, utilizing data related to exercise, sleep, stress, and other aspects of everyday life.
Research Topics
- Exercise and health support
- Stress management and behavior change
- Interaction and input assistance
- Training support
Prospective International Students
We welcome highly motivated international students who are interested in pursuing research in our laboratory.
Our research covers network services, artificial intelligence, human-computer interaction, and real-world computing. In particular, we currently focus on AI and large language models (LLMs), information exploration, collaborative systems, and human activity support, built upon the foundations of distributed and collaborative systems.
Please note that our current research does not primarily focus on distributed algorithms, consensus protocols, replication protocols, or fault-tolerant system infrastructure. Before contacting us, please review our research areas and recent publications to determine whether your interests align with our current research activities.
Due to the large number of inquiries we receive, we may not be able to respond to all inquiries. Priority is given to applicants whose research interests closely match the laboratory’s current research themes.
Contact
For inquiries regarding graduate admission, research opportunities, or international student applications, please contact:
Hideyuki TAKADA, Professor
College of Information Science and Engineering
Ritsumeikan University
Email: