Palo Alto, CA, United States of America

Paul K Mazaika


Average Co-Inventor Count = 1.5

ph-index = 1

Forward Citations = 11(Granted Patents)


Company Filing History:


Years Active: 2004-2011

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2 patents (USPTO):Explore Patents

Title: Paul K Mazaika: Innovator in Imaging and Data Encoding

Introduction

Paul K Mazaika is a notable inventor based in Palo Alto, CA. He has made significant contributions to the fields of functional magnetic resonance imaging and data encoding. With a total of 2 patents, Mazaika's work showcases his innovative approach to solving complex problems in imaging technology.

Latest Patents

Mazaika's latest patents include a method for robust motion correction for functional magnetic resonance imaging. This computer-implemented method corrects motion and interpolation effects during fMRI analysis. The technique estimates motion on every voxel of the data, allowing for high-accuracy analysis by removing unwanted effects. Additionally, he has developed a method for invisible embedded data using yellow glyphs. This invention encodes digital data in a hardcopy rendering of invisible images made of circularly asymmetric dot patterns. The glyphs are designed to be written onto a recording medium in a way that remains undetectable to the naked eye while being decodable by conventional machinery.

Career Highlights

Throughout his career, Mazaika has worked with prominent organizations such as Xerox Corporation and Leland Stanford Junior University. His experience in these institutions has allowed him to refine his skills and contribute to groundbreaking advancements in technology.

Collaborations

Mazaika has collaborated with esteemed colleagues, including Gary H Glover and Allan L Reiss. These partnerships have further enriched his work and expanded the impact of his inventions.

Conclusion

Paul K Mazaika stands out as an innovative inventor whose contributions to imaging and data encoding continue to influence the field. His patents reflect a commitment to advancing technology and improving accuracy in complex analyses.

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