Seul Ki Yeom

Title: Seul Ki Yeom: Innovator in Energy-Aware Deep Neural Network Compression

Introduction

Seul Ki Yeom is a prominent inventor based in Daejeon, South Korea. He has made significant contributions to the field of deep learning, particularly in the area of energy-efficient neural networks. His innovative approach aims to enhance the performance of deep learning models while minimizing energy consumption.

Latest Patents

Seul Ki Yeom holds a patent for a "Method and apparatus for energy-aware deep neural network compression." This patent discloses a method that includes measuring importance scores of a network unit using an energy-based criterion. The process involves performing network pruning of the deep learning model based on these importance scores, thereby optimizing the model for energy efficiency.

Career Highlights

Seul Ki Yeom is currently employed at Nota, Inc., where he continues to develop cutting-edge technologies in the realm of artificial intelligence. His work focuses on creating solutions that balance performance and energy consumption, which is crucial in today's technology-driven world.

Collaborations

Some of his notable coworkers include KyungHwan Shim and Myungsu Chae, who contribute to the innovative environment at Nota, Inc. Their collaborative efforts enhance the research and development of energy-aware technologies.

Conclusion

Seul Ki Yeom's contributions to energy-aware deep neural network compression represent a significant advancement in the field of artificial intelligence. His innovative methods not only improve model efficiency but also address the growing concern of energy consumption in technology.