Ramla, Israel

Shalom Elkayam

USPTO Granted Patents = 7 

 

Average Co-Inventor Count = 2.9

ph-index = 2

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2021-2025

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7 patents (USPTO):Explore Patents

Title: Shalom Elkayam: Innovator in Semiconductor Examination Technologies

Introduction

Shalom Elkayam is a prominent inventor based in Ramla, Israel, known for his contributions to the field of semiconductor examination technologies. With a total of 7 patents to his name, Elkayam has made significant strides in utilizing machine learning to enhance the inspection processes of semiconductor specimens.

Latest Patents

Elkayam's latest patents include innovative systems and methods that leverage machine learning for the examination of semiconductor specimens. One notable patent describes a method for runtime examination of a semiconductor specimen, which involves obtaining a runtime image with a low signal-to-noise ratio (SNR) and processing it using a machine learning model. This model is trained with samples that share design patterns with the inspection area, allowing for accurate examination data specific to various applications. Another patent focuses on generating training data for a Deep Neural Network (DNN) used in semiconductor examination. This method includes extracting features from training images and training a machine learning model to create segmentation maps, which are crucial for improving the accuracy of semiconductor inspections.

Career Highlights

Shalom Elkayam is currently employed at Applied Materials Israel Limited, where he continues to develop cutting-edge technologies in semiconductor examination. His work has positioned him as a key figure in the integration of machine learning within the semiconductor industry, driving advancements that enhance inspection accuracy and efficiency.

Collaborations

Elkayam collaborates with talented professionals in his field, including Shaul Cohen and Tal Ben-Shlomo. These partnerships foster an environment of innovation and creativity, contributing to the development of groundbreaking technologies.

Conclusion

Shalom Elkayam's contributions to semiconductor examination through machine learning exemplify the intersection of technology and innovation. His patents and ongoing work at Applied Materials Israel Limited highlight his commitment to advancing the field and improving inspection methodologies.

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