Vasteras, Sweden

Sinisa Zubic

USPTO Granted Patents = 1 

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Sinisa Zubic: Innovator in Machine Learning for Power Systems

Introduction

Sinisa Zubic is a notable inventor based in Vasteras, Sweden. He has made significant contributions to the field of machine learning, particularly in the context of power system controllers. His innovative approach combines advanced computational techniques with practical applications in industrial automation.

Latest Patents

Sinisa Zubic holds a patent for a "Method and computer system for generating a decision logic for a controller." This invention utilizes machine learning (ML) with labeled data to train a model that generates decision logic for an Industrial Automation Control System (IACS), specifically targeting power system controllers. The ML model is designed with inputs and outputs, and it is decomposed into multiple computational sub-processes. Intermediate signals from one sub-process are fed into the next, allowing for the generation of information based on these signals, which can be interpreted, verified, visualized, and inspected.

Career Highlights

Sinisa Zubic is currently employed at Hitachi Energy Ltd., where he continues to develop innovative solutions in the field of energy and automation. His work focuses on enhancing the efficiency and reliability of power systems through advanced machine learning techniques.

Collaborations

Sinisa has collaborated with several talented individuals in his field, including Jan Poland and Adamantios Marinakis. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Sinisa Zubic's contributions to machine learning and power systems exemplify the impact of innovation in modern technology. His patent and ongoing work at Hitachi Energy Ltd. highlight his commitment to advancing the field and improving industrial automation.

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