Jonathan Holt

Title: Innovations of Jonathan Holt

Introduction

Jonathan Holt is an accomplished inventor based in Sachse, TX (US). He has made significant contributions to the field of machine learning, particularly in variable selection and process control modeling. With a total of 2 patents, his work has garnered attention for its innovative approaches to complex problems.

Latest Patents

Holt's latest patents include "Machine learning variable selection and root cause discovery by cumulative prediction." This invention involves a sequence of models that accumulates r-squared values for an increasing number of variables, quantifying the importance of each variable in predicting a targeted yield or parametric response. Another notable patent is "Die level product modeling without die level input data." This machine learning model imputes process control parameters at the die level, utilizing wafer sort parametric measurements across multiple test sites and yield results for improved analysis of outlier spatial patterns.

Career Highlights

Jonathan Holt is currently employed at Pdf Solutions, Incorporated, where he applies his expertise in machine learning to enhance product modeling and yield analysis. His innovative work has positioned him as a key figure in the industry, contributing to advancements in technology and process optimization.

Collaborations

Holt collaborates with talented individuals such as Richard Gene Burch and Qing Zhu, further enriching the innovative environment at Pdf Solutions, Incorporated.

Conclusion

Jonathan Holt's contributions to machine learning and product modeling demonstrate his commitment to innovation and excellence in his field. His patents reflect a deep understanding of complex systems and a drive to improve processes, making him a notable inventor in today's technological landscape.