This inventor holds 1 USPTO granted patent. Top assignee: Electronics and Telecommunications Research Institute. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2026
Title: Eui Seong Seo: Innovator in Machine Learning Cluster Configuration
Introduction
Eui Seong Seo is a prominent inventor based in Daejeon, South Korea. He has made significant contributions to the field of machine learning, particularly in optimizing power consumption in GPU servers. His innovative approach has the potential to enhance the efficiency of machine learning services.
Latest Patents
Eui Seong Seo holds a patent titled "Method and apparatus for configuring cluster for machine learning service based on minimizing power consumption of GPU servers." This patent outlines a method for configuring a cluster by assigning graphics processing unit (GPU) servers in a cloud environment. The method focuses on measuring the power consumption characteristics of each GPU server for various machine learning models. By utilizing these characteristics, the system assigns GPU servers to optimize power usage while executing multiple machine learning services.
Career Highlights
Eui Seong Seo is affiliated with the Electronics and Telecommunications Research Institute, where he conducts research and development in advanced technologies. His work has been instrumental in pushing the boundaries of machine learning applications and improving the sustainability of GPU server usage.
Collaborations
Eui Seong Seo has collaborated with notable colleagues, including Sung In Jung and Jun Yeol Yu. Their combined expertise has contributed to the advancement of innovative solutions in the field of machine learning.
Conclusion
Eui Seong Seo's contributions to the field of machine learning and his innovative patent demonstrate his commitment to enhancing technology while minimizing energy consumption. His work is paving the way for more efficient machine learning services in the future.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
