Miamisburg, OH, United States of America

Kefan Huang

USPTO Granted Patents = 1 

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: The Innovative Contributions of Kefan Huang

Introduction

Kefan Huang is a notable inventor based in Miamisburg, OH (US). He has made significant strides in the field of energy management and smart thermostat technologies. His work focuses on enhancing the performance of HVAC systems through innovative methods and control systems.

Latest Patents

Kefan Huang holds a patent for "Energy management and smart thermostat learning methods and control systems." This patent describes a method of HVAC system performance monitoring using a computing device connected to at least one thermostat of an HVAC system in a building. The method includes receiving thermostat data, which consists of temperature setpoint data, measured building temperature data, and HVAC operation data for a specific time period. Additionally, weather data is obtained from a weather service for the same time period, and the thermostat data is synchronized with the weather data. A machine learning model is then trained using the synchronized data, allowing for the monitoring of HVAC system performance over time.

Career Highlights

Kefan Huang is currently employed at Copeland Comfort Control LP, where he continues to develop innovative solutions in HVAC technology. His expertise in energy management has positioned him as a valuable asset in the industry.

Collaborations

Kefan has collaborated with notable colleagues, including Brian Richard Butler and Kevin Patrick Hallinan. These partnerships have contributed to the advancement of HVAC technologies and energy management systems.

Conclusion

Kefan Huang's contributions to energy management and smart thermostat technologies demonstrate his commitment to innovation in the HVAC industry. His patent and ongoing work at Copeland Comfort Control LP highlight the importance of integrating machine learning with traditional systems to enhance performance and efficiency.

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