Pohang, South Korea

Younghoon Byun

This inventor holds 1 USPTO granted patent. Top assignee: Pohang University of Science and Technology Foundation. Active years: 2023.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Younghoon Byun. Retrieved from https://idiyas.com/inventor/younghoon-byun

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Younghoon Byun: Innovator in Neural Processing Technology

Introduction

Younghoon Byun is a notable inventor based in Pohang-si, South Korea. He has made significant contributions to the field of neural processing technology. His innovative work focuses on enhancing the efficiency and accuracy of neural networks.

Latest Patents

Younghoon Byun holds a patent for a neural processing device and its operation method. This device includes a noise classifier that preprocesses input data to determine its noise characteristics. Additionally, it features a network selector that chooses one of several neural networks based on these characteristics. An operator then performs inference on the input data using selected weights corresponding to the chosen neural network.

Career Highlights

Younghoon Byun is affiliated with the Postech Academy-Industry Foundation, where he continues to advance his research and development efforts. His work has garnered attention for its potential applications in various technological fields.

Collaborations

Some of his notable coworkers include Youngjoo Lee and Sunggu Lee, who contribute to the collaborative environment at the Postech Academy-Industry Foundation.

Conclusion

Younghoon Byun's innovative contributions to neural processing technology highlight his role as a key inventor in this evolving field. His work promises to influence future advancements in neural network applications.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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