Fremont, CA, United States of America

Wen Jin

USPTO Granted Patents = 15 

Average Co-Inventor Count = 3.7

ph-index = 6

Forward Citations = 71(Granted Patents)


Location History:

  • Sunnyvale, CA (US) (2005 - 2009)
  • Fremont, CA (US) (2013 - 2023)

Company Filing History:


Years Active: 2005-2023

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15 patents (USPTO):Explore Patents

Title: **Innovator Spotlight: Wen Jin - A Leader in Machine Learning Patents**

Introduction

Wen Jin, based in Fremont, California, is an accomplished inventor with an impressive portfolio of 15 patents to his name. His innovative work primarily focuses on enhancing machine learning models and their applications, showing a substantial impact on data analysis and artificial intelligence.

Latest Patents

Wen Jin's latest patents highlight his expertise in the field of machine learning. One of his notable inventions is titled "Determining Confident Data Samples for Machine Learning Models on Unseen Data." This patent outlines techniques for extracting feature vectors and employing an outlier detection model to determine the relevance of unseen data samples in relation to the training dataset. Another significant patent is focused on "Data-Driven Deep Learning Model Generalization Analysis and Improvement." This invention provides methods to evaluate data-driven deep learning models, ensuring that target datasets align with the training dataset for optimal accuracy in applications.

Career Highlights

Throughout his career, Wen Jin has contributed significantly to leading technology firms such as Tokyo Electron Limited and Timbre Technologies, Inc. His innovative approach and profound understanding of machine learning have undoubtedly propelled his career forward, making him a respected figure among his peers.

Collaborations

Wen has had the opportunity to work alongside talented colleagues such as Junwei Bao and Shifang Li. Collaborating with skilled individuals in the field underscores the collective effort required to drive innovation in technology.

Conclusion

Wen Jin's contributions to machine learning and data analysis through his patents reflect not only his mastery of the subject but also his commitment to advancing technology. As he continues to innovate, the implications of his work will likely lead to significant advancements in the way machine learning models are developed and applied in various industries.

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