Basic cluster (B cluster)
Research and Industry-University Collaboration
研究・産学連携
Topics
- 2024.04.09
The research findings on "Optimization Design of Semiconductor Mask Patterns," a collaborative research conducted by researchers from the University of Aizu, Tokyo Institute of Technology, and Kioxia Corporation, were featured in Nikkei xTECH.
Studies and Collaborations - 2024.03.28
The University of Aizu Smart Design Research Cluster and Fukushima Museum held a joint research results presentation
Studies and Collaborations - 2023.09.01
UoA Joint Research Forum 2023 will be held
Studies and Collaborations - 2022.08.29
UoA Joint Research Forum 2022 was held.
Studies and CollaborationsEvent Report - 2022.07.28
UoA Joint Research Forum 2022
News ReleaseStudies and Collaborations
About Basic Cluster
The Basic Cluster is a budding, strategic research team and is expected to transition to the CAIST cluster as the team-based research progresses.
Advanced Networking
Enable secure, scalable and smart network connectivity in a variety of computing systems.
Satellite Data Utilization
Using remote sensing data acquired by earth observation satellites, develop algorithms and software using these algorithms to integrate manual and computational analysis methods.
Smart Design
By innovating methods for describing and manipulating knowledge, a system in which humans can control the automation and capabilities offered by computers is realized.
Automatic AI System Design
Our research is aimed at analyzing and solving difficult tasks in machine learning and deep learning, and automating a series of processes such as design, development, operation, and management of AI systems. With the help of generative Large Language Models (LLMs) we are developing tools for easy AI application creation and administration by a wide range of non-experts which aims to promote AI technology adoption in the society.
Information Security
As society becomes rapidly dependent on IT, information security becomes increasingly important. We aim to create a society where people can use IT safely through extensive research on information security, including the theory and application of cryptography, IoT security such as automobiles and robots, the privacy of big data and AI, and system management. We also focus on human resource development through industry-government-academia collaboration.
Biomedical Information Engineering
Biomedical Information Engineering Cluster is endeavoring in studying and developing the acquisition and analysis technology of biomedical signals, images, and medical information from genes to organs to discover the mechanisms of diseases like heart diseases and cancer; therefore, realize the prevention, early diagnosis, and precision therapy of these diseases to reduce adult diseases, improve ageing health, and lower medical cost for the promotion of human health and welfare.
Data Science and Engineering
We are working on the challenges faced by real-world services using diverse data science techniques, including mathematical models, machine learning, and information visualization, in collaboration with the University-Business Innovation Center (UBIC). A major challenge is returning academic knowledge to society while exploring partnership objectives and collaborative networks that result in a win-win situation for partners and the university.
Intelligent Transportation Systems
Japan Road Transportation and Information Center (JARTIC) has set up a large-scale nationwide sensor network to monitor traffic congestion in Japan. The goal of this cluster is twofold. First, develop an appropriate Society 5.0 cloud-based data lakehouse to store and process voluminous data. Second, investigate novel machine learning techniques to develop a beyond-visual range route recommender system to improve autonomous driving in large-scale transportation networks.
High Performance Computing & Simulation
ARC-HPC cluster will establish a research platform for High Performance Computing (HPC) and Quantum Computing (QC) at our university. Based on the research platform, we will investigate new algorithms for HPC, QC, and large-scale numerical simulations of our universe.