Seung Jae Shin

Title: Seung Jae Shin: Innovator in Federated Learning and Reinforcement Scheduling

Introduction

Seung Jae Shin is a prominent inventor based in Daejeon, South Korea. He has made significant contributions to the fields of federated learning and reinforcement learning through his innovative patents. With a total of two patents to his name, Shin is recognized for his work at the Electronics and Telecommunications Research Institute.

Latest Patents

Shin's latest patents include a "Federated learning device interworking with mobile core system and method thereof." This invention relates to a method for federated learning that interacts with a mobile core system. The method involves querying terminal information from multiple terminals, assessing network performance, selecting participating terminals based on this information, and integrating parameters after local learning.

Another notable patent is the "Apparatus and method for altruistic scheduling based on reinforcement learning." This invention outlines an altruistic scheduling apparatus that includes an external scheduling agent, an internal scheduling agent, and a leftover scheduling agent. The apparatus aims to enhance fairness in scheduling while improving performance indicators such as completion time and efficiency.

Career Highlights

Seung Jae Shin has established himself as a key figure in the research community, particularly in the realm of telecommunications and artificial intelligence. His work has implications for improving network efficiency and resource allocation in various technological applications.

Collaborations

Shin collaborates with talented individuals such as Seung Hyun Yoon and Tae Yeon Kim. These partnerships contribute to the innovative environment at the Electronics and Telecommunications Research Institute.

Conclusion

Seung Jae Shin's contributions to federated learning and reinforcement scheduling highlight his role as an influential inventor in the technology sector. His patents reflect a commitment to advancing the field and improving system efficiencies.