Tokyo, Japan

Keiichiro Kobuchi

USPTO Granted Patents = 3 

 

Average Co-Inventor Count = 4.9

ph-index = 1


Company Filing History:


Years Active: 2024

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3 patents (USPTO):Explore Patents

Title: Keiichiro Kobuchi: Innovator in Control Systems

Introduction

Keiichiro Kobuchi is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of control systems, holding a total of 3 patents. His work focuses on developing advanced control apparatuses that utilize machine learning to enhance operational efficiency.

Latest Patents

Kobuchi's latest patents include innovative technologies such as a control apparatus, control method, and recording medium having a control program recorded thereon. This control apparatus is designed to manage a control target using a machine-learned control model. It outputs an operation amount based on the current state of the equipment. Additionally, it features a prediction unit that forecasts future states of the equipment, an adjusting unit that modifies the operation amount based on predictions, and an output unit that communicates the adjusted operation amount to the control target. Another patent involves a control apparatus that simulates the state of the equipment when the operation amount is applied, allowing for enhanced control and decision-making.

Career Highlights

Kobuchi is currently employed at Yokogawa Electric Corporation, where he continues to innovate in the field of control systems. His work has been instrumental in advancing the capabilities of control technologies, making them more efficient and reliable.

Collaborations

Throughout his career, Kobuchi has collaborated with notable colleagues such as Hiroaki Kanokogi and Yota Furukawa. These partnerships have fostered a creative environment that encourages the development of cutting-edge technologies.

Conclusion

Keiichiro Kobuchi is a distinguished inventor whose work in control systems has led to significant advancements in technology. His innovative patents and collaborations reflect his commitment to enhancing operational efficiency through machine learning.

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