Profile
In 2010, I completed the Master’s Program in Quantum and Materials Engineering at the Graduate School of Electro-Communications, The University of Electro-Communications. After working at NEXT Co., Ltd. (now LIFULL Co., Ltd.) and Neo Career Co., Ltd., I joined the Matsuo-Iwasawa Laboratory at the University of Tokyo in 2019. As an infrastructure engineer supporting machine learning and deep learning research and development, I have been involved in the design, implementation, and operation of GPU/HPC computing infrastructure, cloud environments, networks, information security, and research IT infrastructure. My experience spans a wide range of computing environments, from on-premises GPU servers and university and public supercomputing resources to cloud platforms such as AWS, Google Cloud, and Microsoft Azure, designing and operating infrastructure according to the scale and requirements of research and development projects. I have also worked on IT infrastructure and governance for the secure and efficient operation of AI research organizations, including ISMS, authentication and identity management, SaaS management, and research data management. Currently, I am extending my experience in GPU/HPC, cloud computing, networking, security, and operations into the field of Physical AI. My interests include AI platforms and RobotOps that provide end-to-end support for the collection, transfer, and storage of data generated by robots and sensors, large-scale GPU-based training, and model management and deployment.
Research Interests
AI Research and Development Infrastructure
Platforms that enable researchers and engineers to develop and run large-scale AI models while minimizing the need to deal directly with the complexity of underlying infrastructure such as GPUs and distributed systems.
Physical AI / RobotOps
Platform architectures for Physical AI that securely and efficiently connect the entire lifecycle of large-scale data generated by remote robots and sensors—from data collection and transfer to storage, training, evaluation, and model deployment.
AI for Operations
Systems that leverage LLMs and AI agents to automate and enhance infrastructure operations, information security, ISMS processes, IT service management, and related operational workflows.