Fayetteville, AR, United States of America

Christy Dunlap

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: University of Arkansas. 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: Christy Dunlap: Innovator in Cooling System Fault Detection

Introduction

Christy Dunlap is a notable inventor based in Fayetteville, AR (US). She has made significant contributions to the field of cooling systems through her innovative patent. Her work focuses on utilizing deep learning techniques to enhance the reliability and efficiency of cooling systems.

Latest Patents

Christy Dunlap holds a patent for a groundbreaking method titled "Detecting or predicting system faults in cooling systems in a non-intrusive manner using deep learning." This invention involves a computer-implemented method, system, and computer program product designed to detect or predict system faults in cooling systems. The method employs a deep learning model that is trained to analyze acoustic emission signals and imaging signals to identify potential faults. By using non-intrusive sensors such as hydrophones, microphones, and optical sensors, the system can effectively monitor cooling systems without disrupting their operation.

Career Highlights

Christy Dunlap is affiliated with the University of Arkansas, where she continues to advance her research in the field of cooling systems. Her innovative approach to fault detection has positioned her as a leader in her area of expertise. With a patent portfolio that includes 1 patent, she is recognized for her contributions to technology and engineering.

Collaborations

Christy has collaborated with esteemed colleagues such as Han Hu and Hari Pandey. These partnerships have further enriched her research and development efforts, leading to advancements in cooling system technologies.

Conclusion

Christy Dunlap's work exemplifies the intersection of innovation and technology in the field of cooling systems. Her contributions through her patent demonstrate the potential of deep learning in enhancing system reliability. As she continues her research at the University of Arkansas, her impact on the industry is expected to grow.

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