Yulia Krasilshchikov

Title: Yulia Krasilshchikov and Semiconductor Defect Examination

Introduction

Yulia Krasilshchikov is an inventor associated with Rehovot, Israel, and Applied Materials Israel Limited. Her patent work addresses machine-learning methods for examining defects in semiconductor specimens.

Latest Patents

The provided information lists one patent for Krasilshchikov: “Fourier Transform Based Machine Learning for Defect Examination of Semiconductor Specimens.” The invention describes obtaining an input image that represents differences between an inspection image and its corresponding reference image. A trained machine-learning system processes that image to produce an output defect map showing candidate defects of interest.

The system uses multiple machine-learning models connected and trained together to detect defects based on Fourier transforms. The resulting map can support further examination of the semiconductor specimen. Krasilshchikov is credited with 1 patent.

Career Highlights

Krasilshchikov’s listed patent connects her work with semiconductor inspection and machine-learning-based defect detection. The invention focuses on analyzing image differences to help identify defects of interest.

Collaborations

The supplied information identifies Applied Materials Israel Limited as Krasilshchikov’s company and Eli Kaminsky as a coworker. These details provide context for her professional associations, though no specific roles or contributions are provided.

Conclusion

Yulia Krasilshchikov’s listed invention applies Fourier-transform-based machine learning to semiconductor defect examination, aiming to generate useful defect maps for further analysis.