Minneapolis, MN, United States of America

Yaobin Qin


Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2024-2025

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2 patents (USPTO):

Title: Innovations of Yaobin Qin in Data Deduplication

Introduction

Yaobin Qin is a notable inventor based in Minneapolis, MN, who has made significant contributions to the field of data deduplication. With a total of two patents to his name, Qin's work focuses on enhancing the efficiency and effectiveness of data backup systems. His innovative approaches leverage machine learning techniques to improve performance in data management.

Latest Patents

Yaobin Qin's latest patents include "Methods and systems for improved deduplication performance using prefetched backup information" and "Methods and systems for affinity aware container prefetching." The first patent outlines a method that generates new feature information for backup images and compares it with existing images to identify and prefetch relevant data. This process utilizes machine learning to enhance deduplication performance. The second patent introduces techniques for deduplication that involve generating container range information and determining container range affinity to optimize data retrieval.

Career Highlights

Qin is currently employed at Veritas Technologies LLC, a company renowned for its data management solutions. His role involves developing advanced methods that streamline data backup processes and improve overall system performance. His expertise in machine learning and data management has positioned him as a valuable asset in the tech industry.

Collaborations

Yaobin Qin collaborates with Xianbo Zhang, working together to advance their research and development efforts in data deduplication technologies. Their combined expertise contributes to innovative solutions that address the challenges of data management.

Conclusion

Yaobin Qin's contributions to the field of data deduplication through his innovative patents and work at Veritas Technologies LLC highlight his significant impact on improving data management systems. His focus on leveraging machine learning techniques sets a precedent for future advancements in this critical area of technology.

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