San Jose, CA, United States of America

Jerry Lin

USPTO Granted Patents = 5 

Average Co-Inventor Count = 6.5

ph-index = 2

Forward Citations = 7(Granted Patents)


Company Filing History:


Years Active: 2019-2022

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5 patents (USPTO):

Title: Jerry Lin: Innovator in Predictive Systems

Introduction

Jerry Lin is a prominent inventor based in San Jose, CA, known for his contributions to predictive systems and matrix analysis. With a total of 5 patents, he has made significant strides in the field of technology, particularly while working at Microsoft Technology Licensing, LLC.

Latest Patents

One of Jerry Lin's latest patents is focused on predicting feature values in a matrix. This invention discloses systems and methods for accessing a matrix with multiple dimensions, where one dimension represents features and another represents entities. The server involved in this process separates the matrix into multiple submatrices along a first dimension, allowing for efficient computation of correlations between values. This correlation is crucial for predicting the value of a preselected feature based on other values in the matrix. Another notable patent by Lin is also centered on negative sampling, which employs similar methodologies to enhance predictive accuracy.

Career Highlights

Throughout his career, Jerry Lin has demonstrated a strong commitment to innovation and technology. His work at Microsoft Technology Licensing, LLC has positioned him as a key player in the development of advanced predictive systems. His patents reflect a deep understanding of complex data structures and their applications in real-world scenarios.

Collaborations

Jerry Lin has collaborated with talented individuals such as Benjamin John McCann and Skylar Payne, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Jerry Lin's contributions to the field of predictive systems through his patents and collaborative efforts highlight his role as a significant inventor in the technology sector. His work continues to influence advancements in matrix analysis and predictive modeling.

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