Riccardo Emanuele Sarpietro

Title: Riccardo Emanuele Sarpietro: Innovator in Machine Learning Techniques for Wafer Defect Classification

Introduction

Riccardo Emanuele Sarpietro is an inventor based in Paterno, Italy. He has made significant contributions to the field of machine learning, particularly in the classification of wafer defect maps. His innovative approach utilizes advanced techniques to enhance the accuracy of defect detection in semiconductor manufacturing.

Latest Patent Applications

Riccardo Emanuele Sarpietro has submitted a patent application titled "MACHINE LEARNING TECHNIQUES FOR WAFER DEFECT MAP CLASSIFICATION." This application outlines various embodiments that provide methods, apparatus, systems, and computing devices for generating classification predictions for wafer defect maps. The process involves generating reduced feature data using a non-linear dimensionality reduction machine learning model, based on vector representations for a set of wafer defect map images. Additionally, the application describes the generation of one or more wafer defect pattern clusters using a density-based clustering machine learning model, which is based on the reduced feature data. Each wafer defect map image is associated with a specific wafer defect pattern cluster, allowing for accurate classification predictions.

Conclusion

Riccardo Emanuele Sarpietro is an emerging inventor in the realm of machine learning applications for semiconductor technology. His work aims to improve the efficiency and accuracy of wafer defect classification, showcasing the potential of innovative techniques in this critical industry.