Award
Mr. Olinga Toh Raoul Joseph, a second-year master's student, has received A registration bursary for CISTM17 award from International Society of Travel Medicine.
Connecting People and Society through AI
ETL Project
Since its establishment, our laboratory has pursued research that harnesses ICT, AI, and Data Science to address real-world challenges in healthcare, nursing, elderly care, education, and environmental sustainability.
Our mission is to break down barriers in language, learning, health, and multicultural communication, creating technologies that empower people and contribute to a more inclusive and resilient society.
Natural Language Processing:
Connecting People and Society Through Language
Artificial intelligence has reached a stage where it can understand, generate, and translate human language with remarkable accuracy. Language technologies are transforming the way people access information, communicate, and learn.
Our research focuses on Natural Language Processing (NLP) and Large Language Models (LLMs) to bridge communication gaps, discover insights from textual data, and improve access to information for diverse communities.
Research Topics
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Automated detection of fake news for a more trustworthy information society
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Automatic question-answer generation from books to support reading and knowledge access
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Sentiment and opinion mining from social media
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Translation between Okinawan dialects and Standard Japanese using LLMs
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Language technologies for preserving regional and minority languages
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Natural language-based academic paper retrieval and search algorithms
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Stock market trend prediction from news articles and financial texts
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Named entity recognition and information extraction for Japanese texts
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Japanese language proficiency assessment using large language models
Through these studies, we aim to develop AI technologies that make information more accessible, support multilingual communication, and contribute to a more inclusive society.
Education and Computing
Designing the Future of Learning
The rapid advancement of generative AI and digital technologies is transforming the way people learn.
Our research focuses on education and computing, with the goal of creating effective learning methods and environments tailored to the needs of individual learners. By combining educational theory, learning sciences, and emerging technologies, we seek to enhance learning experiences and improve educational outcomes.
Research Topics
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Personalized learning support based on learner characteristics and needs
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Analysis of collaborative learning and Project-Based Learning (PBL) effectiveness
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Curriculum design utilizing microlearning approaches
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Development of AI-powered learning support systems
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Investigation of the impact of AI on learners’ cognition and thinking processes
Through these studies, we aim to build innovative educational environments that support lifelong learning and prepare learners for an AI-driven society.
Diversity Channel
Many foreign residents in Japan face difficulties accessing essential information related to healthcare, elderly care, and education, often leading to uncertainty and social isolation.
Diversity Channel is a project that leverages multilingual technologies and artificial intelligence to make important information accessible and understandable to everyone, regardless of language or cultural background.
Key Initiatives
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Multilingual dissemination of healthcare and elderly care information
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Automatic generation of Q&A content from specialized books and publications
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Development of chatbots for foreign residents in Japan
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Information delivery using Plain Japanese (Yasashii Japanese)
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AI-powered multilingual document generation
By utilizing Natural Language Processing (NLP) and Generative AI technologies, we aim to reduce information disparities arising from linguistic and cultural differences and contribute to a more inclusive society for diverse communities.
Medical Informatics
Using AI to Advance Personalized Healthcare
Genomic and medical data contain valuable clues for predicting disease onset and progression.
In our laboratory, we leverage machine learning and artificial intelligence (AI) to conduct research in:
• Cancer diagnosis support
• Survival prediction
• Disease risk estimation
• Personalized medicine support
Research Examples
• A breast cancer survival prediction model using genomic data
• A liver cancer diagnosis model based on gene expression data
Our long-term goal is to support healthcare professionals in their decision-making and contribute to a future where personalized healthcare is available to every individual.
Research in Past
I conducted research to support education and the environment. As for education, I am mainly involved in programming education and e-learning. As for education, I am now mainly engaged in promoting information education at the Information Processing Society of Japan (IPSJ) Information Education Committee.
Information/お問い合わせ
東京都千代田区紀尾井町7-1