San Francisco, CA, United States of America

Michael James Kanellos


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Michael James Kanellos: Innovator in Brain-Computer Interface Technology

Introduction

Michael James Kanellos is a prominent inventor based in San Francisco, CA. He is known for his groundbreaking work in the field of brain-computer interfaces. His innovative approach has the potential to revolutionize how humans interact with technology.

Latest Patents

Kanellos holds a patent for a brain-computer interface device, system, and operating method. This patent describes a method and apparatus to control the operation of a brain-computer interface. The process involves capturing a time series of brain activity in response to stimuli, passing this data to a history-based challenge generator, and issuing challenges to the user. The system captures brain responses to these challenges and compares them to predicted responses, ensuring accurate interaction with the interface. This invention highlights Kanellos's commitment to advancing technology that bridges the gap between human cognition and machine operation. He has 1 patent to his name.

Career Highlights

Kanellos has made significant contributions to the field of technology through his work at Arm Limited. His role at the company allows him to collaborate with other talented professionals and push the boundaries of innovation. His expertise in brain-computer interfaces positions him as a leader in this emerging field.

Collaborations

Throughout his career, Kanellos has worked alongside notable colleagues such as Remy Pottier and Hugo John Martin Vincent. These collaborations have fostered an environment of creativity and innovation, further enhancing the development of cutting-edge technologies.

Conclusion

Michael James Kanellos is a visionary inventor whose work in brain-computer interfaces is paving the way for future advancements in technology. His contributions are not only significant but also essential for the evolution of human-computer interaction.

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