Ritsumeikan University Researcher Database
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(Last updated : 2023-05-15 15:00:36)
LI HENGYI
Department / Course
Research Organization of Science and Technology
Title / Position
Senior Researcher
Achievement
Other Affiliations
Profile
Academic background
Business career
Committee and society
Research activities
Qualification and license
Subject of research
Research summary
Research summary(Photo/Image)
Present specialized field
research
Books
Papers
Others
Academic conference presentation
Other research achievements
Works
Winning science prize
Grants-in-Aid for Scientific Research -KAKENHI-
Competitive grants, etc. (exc. KAKENHI)
Achievements of joint.Funded research
Acquisition patent
Ritsumeikan Research Funding
teaching
Subject
Teaching achievements
social activity
Activity in society
Research exchange preferred theme
Others
Message
Home Page
E-Mail Address
Department laboratory expense researcher number
researchmap Researcher code
External Researcher ID
Academic background
1.
2020/04~2023/03
Doctorial Course │ Major in Advanced Electrical, Electronic and Computer Systems │ Graduate School, Division of Science and Engineering │ Ritsumeikan University │ Completed Doctor of Engineering
2.
2007/09~2011/07
Major in Automation │ School of Electronic and Informatio │ Zhongyuan University of Technology │ Graduated Bachelor of Engineering
Business career
1.
2011/07 ~ 2020/03
Senior Experimentalist │ School of Electronic and Information │ School of Electronic and Information
Research activities
1.
2022/10 ~
Institute of Electrical and Electronics Engineers
Subject of research
1.
Computer architecture and high performance computing for artificial intelligence
Research summary
Auto-Generation of Optimal Al Models with High-Performance Computing
Artificial Intelligence (AI) has promoted breakthrough progress for nearly all over domains. However, the current yet comprehensive AI theory that especially lacks precise guidance in designing high-efficient networks, heavy workload which demands huge amount of hardware resource, seriously overparameterization with significant number of redundancies, have been severe obstacles that impede the further high-efficient application of AI. The research aims to improve the current AI theory to provide theoretical foundation for designing high-performance deep neural networks (DNNs), and further develop an automatic system for implementing AI applications on target tasks with architecture-level optimization, involving software level and hardware level optimization. The research aims to provide a comprehensive solution for AI applications in various fields, addressing the current obstacles and enabling high-efficiency implementation of AI for targeted tasks
Present specialized field
High performance computing, Electron device and electronic equipment
Message
1.
Welcome to exchange ideas
am currently a senior researcher at Ritsumeikan University. I received my Ph.D. degree from the College of Science and Engineering at Ritsumeikan University in Japan. My research interests lie in the high-performance computing of Artificial Intelligence (AI), FPGA-based accelerator design for AI, and Edge computing.
Over the years, I have been dedicated to advancing the field of AI by designing innovative hardware solutions to accelerate the training and inference of neural networks. I have also been actively involved in research on edge computing, exploring how to enable efficient and secure AI processing at the edge of the network.
As a researcher, I am committed to creating practical and impactful solutions that can benefit society. I believe that AI has the potential to transform various industries and improve people's lives, and I am excited to contribute to this endeavor.
Thank you for considering my self-introduction. Please let me know if you have any further questions or if there is anything else I can assist you with.
E-Mail Address
Department laboratory expense researcher number
70986728
External Researcher ID
ORCID ID
0000 0003 4112 7297