Cary, NC, United States of America

Guixian Lin


Average Co-Inventor Count = 4.4

ph-index = 1

Forward Citations = 8(Granted Patents)


Company Filing History:


Years Active: 2017-2021

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2 patents (USPTO):Explore Patents

Title: Guixian Lin: Innovator in Data Systems and Predictive Modeling

Introduction

Guixian Lin is a notable inventor based in Cary, NC (US), recognized for his contributions to the fields of data systems and predictive modeling. With a focus on enhancing computational efficiency, Lin has developed innovative solutions that address complex data challenges. His work has led to the acquisition of 2 patents, showcasing his expertise and commitment to advancing technology.

Latest Patents

Lin's latest patents include an "Analytic system for gradient boosting tree compression" and "Systems and methods for quantile determination in a distributed data system using sampling." The first patent describes a computing device that compresses a gradient boosting tree predictive model, trained using multiple observation vectors. This model predicts response variable values based on explanatory variable values, and it employs a compression model to minimize the number of trees while maintaining predictive accuracy. The second patent outlines methods for estimating quantiles in a distributed data system, where data is stored across multiple nodes. This system defines data bins and determines quantile bounds to accurately estimate specified quantiles.

Career Highlights

Guixian Lin is currently employed at SAS Institute Inc., a leading company in analytics software and solutions. His role involves leveraging his expertise in data systems to develop innovative technologies that enhance data analysis and predictive modeling capabilities.

Collaborations

Lin has collaborated with notable colleagues, including Xiangqian Hu and Guy Blanc, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Guixian Lin's work exemplifies the intersection of data science and predictive modeling, making significant strides in the field. His patents reflect a deep understanding of complex data systems and a commitment to improving computational methods.

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