Menlo Park, CA, United States of America

John Godlewski

This inventor holds 1 USPTO granted patent and 4 published patent applications. Top assignee: Schlumberger Technology Corporation. Active years: 2026.

USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: John Godlewski: Innovator in Machine Learning Algorithms

Introduction

John Godlewski is a prominent inventor based in Menlo Park, California. He has made significant contributions to the field of machine learning, particularly in the area of flash calculations. His innovative approach has led to the development of a patented method that enhances the efficiency of processing input fluid mixtures.

Latest Patents

John Godlewski holds a patent for "Generalizable machine learning algorithms for flash calculations." This method involves obtaining input data that includes environmental conditions and chemical properties of input components in a fluid mixture. The process includes encoding the input data using an encoder machine learning model, followed by aggregating the encoded data to produce output data that indicates the phase of an output mixture. This innovative approach allows for more efficient data processing and analysis.

Career Highlights

John Godlewski is currently employed at Schlumberger Technology Corporation, where he applies his expertise in machine learning to develop advanced solutions for the energy sector. His work focuses on improving the accuracy and efficiency of chemical processing through innovative algorithms.

Collaborations

John collaborates with fellow inventor John Pang, working together to push the boundaries of technology in their field. Their combined efforts contribute to the advancement of machine learning applications in various industries.

Conclusion

John Godlewski's contributions to machine learning and his innovative patent demonstrate his commitment to advancing technology in the energy sector. His work continues to influence the development of efficient algorithms that enhance data processing capabilities.

Profile summary based on public USPTO records.
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