Raleigh, NC, United States of America

Artin Armagan


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Artin Armagan: Innovator in Deep Learning Classifications

Introduction

Artin Armagan is a notable inventor based in Raleigh, NC (US). He has made significant contributions to the field of deep learning, particularly in the area of request classification. His innovative approach has led to the development of a patented system that enhances the accuracy of real-time request evaluations.

Latest Patents

Artin holds a patent titled "Predicting likelihood of request classifications using deep learning." This patent describes a system and method that involves receiving a first set of variables associated with a real-time request. The process includes extracting a predetermined subset of these variables to generate a second set, identifying historical request data, and computing parameters based on the initial variables and historical data. The system generates numeric and string sequences for the request, converts string sequences into encoded formats, and inputs these into a trained deep machine learning model. Ultimately, it computes a score that indicates the likelihood of the request belonging to an unauthorized classification. Artin has 1 patent to his name.

Career Highlights

Artin is currently employed at SAS Institute Inc., a leading analytics software company. His work focuses on leveraging deep learning techniques to improve classification systems, which is crucial for various applications in data analysis and machine learning.

Collaborations

Artin collaborates with talented colleagues, including Yi Liao and Phoemphun Oothongsap. Their combined expertise contributes to the advancement of innovative solutions in the field of deep learning.

Conclusion

Artin Armagan is a pioneering inventor whose work in deep learning has the potential to transform request classification systems. His contributions are significant in enhancing the accuracy and efficiency of real-time data processing.

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