Pohang-si, South Korea

Cheol-hun Jang


Average Co-Inventor Count = 3.3

ph-index = 2

Forward Citations = 13(Granted Patents)


Company Filing History:


Years Active: 2013-2023

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6 patents (USPTO):Explore Patents

Title: Cheol-hun Jang: Innovator in Neural Networks and Vehicle Control

Introduction

Cheol-hun Jang is a prominent inventor based in Pohang-si, South Korea. He has made significant contributions to the fields of neural networks and vehicle control, holding a total of six patents. His innovative work has the potential to impact various industries, particularly in artificial intelligence and automotive technology.

Latest Patents

Cheol-hun Jang's latest patents include a method of outputting prediction results using a neural network and a method of generating a neural network, along with the necessary apparatus. One of his notable inventions involves generating a second neural network model based on prediction results from a first model, which utilizes unlabeled input data. Additionally, he has developed a method and apparatus for controlling a vehicle using a first model that is trained according to the optimized output of a second model. These advancements showcase his expertise in leveraging neural networks for practical applications.

Career Highlights

Throughout his career, Cheol-hun Jang has worked with esteemed organizations such as Samsung Electronics Co., Ltd. and the Postech Academy-Industry Foundation. His experience in these companies has allowed him to refine his skills and contribute to groundbreaking projects in technology and innovation.

Collaborations

Cheol-hun Jang has collaborated with notable colleagues, including Dae-hyun Ji and Yoon-suk Hyun. These partnerships have fostered a creative environment that encourages the exchange of ideas and the development of innovative solutions.

Conclusion

Cheol-hun Jang is a distinguished inventor whose work in neural networks and vehicle control continues to shape the future of technology. His patents reflect a commitment to innovation and a deep understanding of complex systems.

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