Monterey Park, CA, United States of America

Brain Hang Wai Yang


Average Co-Inventor Count = 3.0

ph-index = 3

Forward Citations = 23(Granted Patents)


Company Filing History:


Years Active: 2006-2010

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4 patents (USPTO):Explore Patents

Title: Brain Hang Wai Yang: Innovator in Network Switching Technology

Introduction

Brain Hang Wai Yang is a notable inventor based in Monterey Park, California. He has made significant contributions to the field of network switching technology, holding a total of four patents. His innovative work focuses on improving the efficiency and functionality of network switches.

Latest Patents

Among his latest patents is the "Output queued switch with a parallel shared memory." This invention describes a network switch that includes an input layer designed to receive a data stream composed of a set of cells. Each cell contains data and a header that designates a destination device. The input layer consists of multiple circuits that work together to assign selected cells to corresponding queues based on their destination. Additionally, Yang's patent for a "Network switch with a parallel shared memory" further enhances the capabilities of network switches by optimizing the routing process through a structured input, intermediate, and output layer system.

Career Highlights

Throughout his career, Brain Hang Wai Yang has worked with prominent companies such as Raza Microelectronics, Inc. and RMI Corporation. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking advancements in network technology.

Collaborations

Yang has collaborated with talented individuals in the field, including Kai-Yeung (Sunny) Siu and Mizanur Mohammed Rahman. These partnerships have fostered a creative environment that has led to innovative solutions in network switching.

Conclusion

Brain Hang Wai Yang's contributions to network switching technology through his patents and collaborations highlight his role as a significant innovator in the field. His work continues to influence advancements in network efficiency and functionality.

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