Sammamish, WA, United States of America

Thomas W Potthast

USPTO Granted Patents = 2 

Average Co-Inventor Count = 11.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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2 patents (USPTO):

Title: Innovative Mind: The Contributions of Thomas W. Potthast

Introduction

Thomas W. Potthast, an accomplished inventor based in Sammamish, WA, has made significant contributions to the field of data processing through his innovations. With two patents to his name, Potthast has demonstrated a keen understanding of technology and its applications in detecting anomalies in data.

Latest Patents

Among his notable inventions is a patent focused on data anomaly detection. This system involves recommending one or more algorithms from a set of algorithms to process received time series data. The recommendations take into account the type of workload involved in processing the data. Additionally, the system provides assisted parameter tuning for detected anomaly alerts and calibration, allowing users to process the data based on a selected algorithm that is parameter tuned for optimal performance.

Career Highlights

Potthast is currently affiliated with Microsoft Technology Licensing, LLC, where he continues to work on innovative solutions that push the boundaries of technology. His work in data anomaly detection demonstrates his commitment to addressing complex challenges in data analysis and enhancing the efficiency of processing time series data.

Collaborations

Throughout his career, Potthast has collaborated with esteemed colleagues such as Richard Wydrowski and Sai Sankalp Arrabolu. These collaborations highlight the importance of teamwork in fostering innovation and developing groundbreaking technologies.

Conclusion

In summary, Thomas W. Potthast's contributions to the field of data processing through his patents and collaborative efforts showcase his inventive spirit. As technology continues to evolve, his work in data anomaly detection will undoubtedly play a crucial role in advancing our understanding of data dynamics and improving the ways we manage and analyze information.

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