RARA Associate Fellow
Automatic Generation & Self-regulatory Updating AI and the Applications for Industry
Automatic Generation & Self-regulatory Updating AI and the Applications for Industry
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FELLOW PROFILE
Serving as a Professor at the Department of Electronic and Computer Engineering, College of Science and Engineering, Ritsumeikan University since 2024. Received his Ph.D. in Science and Engineering from Ritsumeikan University in 2012.
Previously worked as a Research Associate (2011-2012), Assistant Professor (2013-2017), and Lecturer (2018) at the Department of Electronic and Computer Engineering, Ritsumeikan University.
Served as a Visiting Scholar in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities in 2015. A senior member of IEEE and a member of ACM, IPSJ, IEICE, and IEE.
Developing Automatic Generation and Self-regulatory Updating Technology for AI Models for Social Implementation through Interdisciplinary Research with Multiple Fields
The proposal aims to establish new technology for automatic generation and self-regulatory updating to design compact and high-performance AI models. Furthermore, we aim to develop a flexible dataset-creation method to effectively train AI models. In terms of application, we integrate the proposed modern AI technology with robots, IoT, etc., to enhance industrial competitiveness, address societal issues such as labor shortages due to declining birth rates and an aging population, and protect and preserve cultural heritage, among other goals.
Recently, AI technology has been widely used in various fields. However, several issues hinder its applications. Redundant computations, for example, pose a challenge, making it difficult to implement AI in environments with limited hardware resources. In addition, the need for engineers to build AI models makes it difficult to apply AI in industries, particularly in small and medium-sized enterprises facing labor shortages. To address these problems, this research seeks to establish new technology for automatic generation and self-regulatory updating to design compact and high-performance AI models.
The goal of this research is to advance high-level AI research and facilitate its international dissemination. We also aim to apply these AI technologies in practical settings to support industry, protect cultural heritage, and address contemporary social issues. Furthermore, we seek to nurture young researchers, particularly doctoral students, through advanced research opportunities.
We aim to achieve multidisciplinary research by integrating technologies such as AI, IoT, and robotics based on specific needs. Additionally, we plan to strengthen joint research efforts with the United States, China, and India, while enhancing collaboration with top universities and leading researchers.
This research aims to develop cutting-edge AI technology to drive technological advancement. Additionally, we seek to apply the proposed AI technology across multiple fields to contribute to society. For instance, we aim to provide advanced AI technology to small and medium-sized enterprises to enhance their competitiveness, and to apply AI in deciphering ancient literature, contributing to the preservation and organization of cultural heritage. Furthermore, integrating AI with robotics may alleviate the social problem of labor shortages.
Partnerships:
I would like to collaborate with leading AI researchers to pursue advanced research. Regarding applications, I would also to collaborate with companies that require AI to become research partners. Furthermore, I would like to collaborate with naturalists and individuals who own a large amount of undeciphered ancient documents, particularly in the preservation and organization of cultural properties.
Research collaborations:
I think it is important to maintain close communication and understand each other, when collaborating with domestic and overseas universities and research institutes.