Madrid, Spain

Ginés Carrascal De Las Heras


Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2022

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1 patent (USPTO):

Title: The Innovative Mind of Ginés Carrascal De Las Heras

Introduction

Ginés Carrascal De Las Heras, a forward-thinking inventor based in Madrid, Spain, is making significant strides in the intersection of technology and biology. With his expertise in machine learning and spectroscopy, he has developed innovative methods for analyzing biological samples.

Latest Patents

Ginés holds a patent for a groundbreaking process titled "Testing a biological sample based on sample spectrography and machine learning techniques." This patent outlines a computer-implemented method that includes receiving data associated with a dynamic speckle spectrum image of a biological sample. The method involves comparing this image with a series of training images, leading to the classification of any contaminants present in the sample, and providing actionable information about their identity. This innovative approach showcases Ginés' ability to integrate cutting-edge technology with practical applications in the biological field.

Career Highlights

Currently, Ginés is affiliated with International Business Machines Corporation (IBM), where he leverages his skills in innovative research and development. His work at IBM is characterized by a commitment to advancing technological frontiers and contributing to the body of knowledge in machine learning applications.

Collaborations

Throughout his career, Ginés has had the opportunity to collaborate with esteemed colleagues, including Sumit Patel and David Bacarella. These partnerships have enabled him to work on various projects that push the boundaries of what is possible in the realm of biological sample analysis and innovation.

Conclusion

With one notable patent to his name and his ongoing contributions at IBM, Ginés Carrascal De Las Heras is a remarkable inventor whose work exemplifies the fusion of technology and biology. His continued efforts in advancing machine learning techniques pave the way for future innovations in the field.

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