About Us

Our Lab aims to contribute to the succession of cultural heritage and promote the forward of the industry and society by utilizing the core manufacturing technology of Computer Architecture and High-performance Computing, and the advanced techniques including AI, IoT, BigData Analysis.
Main Research Interests :
Hardware: Computer Architecture, Parallel Processing, FPGA, FPGA-DPU, Embedded system(Raspberry pi, Jetson)
Software: AI(Deep Learning), Machine Learning, Image Processing, Big Data Analysis
5 Ph.D. students, 14 master students, and 6 undergraduate students

Notes assigned to the research office in 2021

Contact and Location
Laboratory location: the 1st floor of ROHM Plaza, Intelligent High Performance Computing Laboratory
Email: menglin@fc.ritsumei.ac.jp  

Research Topics

AI + High-Performance Computing(AIHPC)

The research focuses on designing high-performance computing architectures, especially Deep Learning, by hardware platforms such as FPGA.
Deep learning (AI) has been wildly used in various fields. However, the large amount of calculations limits the application, especially in the limited resource experiments. This research topic aims to optimize AI models and improve the performance on both software-level and hardware-level.

AI+ cultural heritage re-organization and protection

The research aims to reorganize and protect the cultural heritage by utilizing the techniques including AI, image processing, and big data analysis.
Generally, we first challenge to implement the automatic extraction and recognition of ancient characters such as skeletal characters, Oracle characters, Rubbing text, and kuzushiji characters by deep learning and image processing. Then, we create a spatiotemporal database for re-organizing ancient literature, and extract the potential knowledge the ancient literature by big data analysis techniques.

AI + IoT (AIoT)

The research aims to realize the accessible AI for the realization the safe-comfortable-convince life whenever and wherever.
In detail, a compact embedded device is applied as an edge device, and data can be obtained conveniently. The edge device also undertakes the light procedure and transforms the data to a server for the further processing. In this way, the IoT brings the crawls to AI. Then, the AI can detect and recognize objects regardless of time and place.

AI + Indestry

These research aims to realize AI applications in various industries.

    ・Automatic cleaning up dishes using AI and Robotics
    ・Real-Time Medicine Packet Recognition System in Dispensing Medicines for The Elderly
    ・Machine learning-based diagnosis assistant of apathy
    ・Mask-wearing status recognition and social distance checking system for COVID-19