Research Topics
We aim to realize self-adaptive systems and multi-agent systems that autonomously monitor and analyze the current situation, consider the next strategy to take, and change their own behavior to achieve their goals. We are also studying next-generation technologies for designing and implementing autonomous software, such as technologies for automating software development and automatically discovering user requirements.
We conduct research on privacy-preserving data mining, a technology that enables the secure utilization of data containing personal information. Our current focus is on federated learning, in which multiple data holders collaboratively build AI models while preserving privacy. We aim to develop novel techniques that achieve a balance between privacy protection and utility.
Life in the Lab
- Members typically come to the lab on weekdays to work on their individual research. Each academic year group holds a weekly seminar where students share updates on their research progress and recent activities.
(The seminar schedule is determined at the beginning of the academic year based on students’ availability and preferences. )
- In the initial phase, students explore multiple academic papers to identify potential research topics, which they present during seminars. Around summer, each student finalizes their research theme and begins refining their topic, conducting experiments, and writing papers.
- Undergraduate students aim to present their work at domestic conferences, while master's students target presentations at international conferences and submissions to academic journals.
