Pittsburgh, PA, United States of America

Pengtao Xie

USPTO Granted Patents = 6 

Average Co-Inventor Count = 2.7

ph-index = 2

Forward Citations = 20(Granted Patents)


Company Filing History:


Years Active: 2018-2023

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6 patents (USPTO):Explore Patents

Title: Innovations of Pengtao Xie

Introduction

Pengtao Xie is a notable inventor based in Pittsburgh, PA, with a significant contribution to the field of industrial process control and machine learning. He holds a total of six patents, showcasing his innovative approach to technology and automation.

Latest Patents

Among his latest patents is the "Autonomous industrial process control system and method that provides autonomous retraining of forecast model." This invention focuses on a system and method for controlling industrial processes, utilizing a forecast model that can autonomously retrain itself without human intervention. The system is designed to trigger retraining and redeployment of the forecast model when its performance degrades, ensuring optimal operation.

Another significant patent is the "Efficient peer-to-peer architecture for distributed machine learning." This invention describes a distributed peer-to-peer system where multiple computers collaborate to run a machine learning program. The system includes various modules, such as a parser module, a parameter replica module, a compressor module, and a communication module, all working together to update the model parameter matrix efficiently.

Career Highlights

Pengtao Xie has worked with prominent companies, including Petuum Inc. and Microsoft Technology Licensing, LLC. His experience in these organizations has allowed him to develop and refine his innovative ideas, contributing to advancements in technology.

Collaborations

Throughout his career, Xie has collaborated with notable individuals such as Eric Xing and Ran Gilad-Bachrach. These collaborations have likely enriched his work and led to further innovations in his field.

Conclusion

Pengtao Xie's contributions to industrial process control and machine learning demonstrate his commitment to innovation and technology. His patents reflect a deep understanding of complex systems and a drive to improve efficiency in industrial applications.

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