Santa Cruz, CA, United States of America

Allan Enemark


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations of Allan Enemark

Introduction

Allan Enemark is a notable inventor based in Santa Cruz, CA (US). He has made significant contributions to the field of technology, particularly in the development of graphical user interfaces. His innovative work has led to the creation of a unique patent that addresses the identification of anomalous patterns in network data.

Latest Patents

Allan Enemark holds a patent for "Finding anomalous patterns." This patent describes technologies for generating a graphical user interface (GUI) dashboard with a three-dimensional (3D) grid of unit cells. The invention allows for the determination of an anomaly statistic for a set of records. It identifies and sorts a subset of network address identifiers according to the anomaly statistic, which can have higher values than other identifiers. The GUI dashboard is organized with unit cells representing network address identifiers as rows, time intervals as columns, and colors indicating configurable anomaly scores. Each unit cell serves as a 3D visual object that represents a composite score of anomaly scores associated with network access events.

Career Highlights

Allan Enemark is currently employed at Nvidia Corporation, a leading company in the field of graphics processing and AI technology. His work at Nvidia has allowed him to further develop his innovative ideas and contribute to cutting-edge technology solutions.

Collaborations

Allan has collaborated with talented coworkers, including Ajay Anil Thorve and Rachel Allen. Their combined expertise has fostered a creative environment that encourages innovation and the development of advanced technologies.

Conclusion

Allan Enemark's contributions to technology through his patent and work at Nvidia Corporation highlight his role as an influential inventor. His innovative approach to identifying anomalous patterns in network data showcases the potential for advancements in graphical user interfaces.

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