Wexford, PA, United States of America

Wan-Yi Lin

USPTO Granted Patents = 14 

Average Co-Inventor Count = 4.5

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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14 patents (USPTO):Explore Patents

Title: Innovations of Wan-Yi Lin

Introduction

Wan-Yi Lin is a prominent inventor based in Wexford, Pennsylvania, known for his significant contributions to the field of machine learning and optimization. With a total of 14 patents to his name, Lin has developed innovative systems that enhance the capabilities of machine learning models and manufacturing processes.

Latest Patents

One of Lin's latest patents is titled "System and method for high-resolution blackbox patch attack with Bayesian optimization." This invention involves a sophisticated system that utilizes Bayesian optimization to generate and iteratively update patches for machine-learning models, ensuring that they meet specific success criteria. Another notable patent is "Methods and systems for training a machine learning model with measurement data captured during manufacturing process." This patent outlines a method for training machine learning models using measurement data from various manufacturing stations, enabling more accurate predictions based on the physical characteristics of manufactured parts.

Career Highlights

Throughout his career, Wan-Yi Lin has worked with esteemed organizations such as Robert Bosch GmbH and Carnegie Mellon University. His experience in these institutions has allowed him to refine his skills and contribute to groundbreaking research in machine learning and optimization.

Collaborations

Lin has collaborated with notable colleagues, including Filipe J Cabrita Condessa and Jeremy Zico Kolter, further enhancing the impact of his work in the field.

Conclusion

Wan-Yi Lin's innovative patents and career achievements highlight his significant role in advancing machine learning technologies. His work continues to influence the industry and pave the way for future innovations.

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