This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: Applied Materials, Inc.. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2026
Title: Innovations by Krishnaprasad Reddy Mallavaram
Introduction
Krishnaprasad Reddy Mallavaram is an accomplished inventor based in Bengaluru, India. He has made significant contributions to the field of machine learning and defect detection in processed wafers. His innovative approach has led to the development of a patented method that enhances the efficiency of defect classification.
Latest Patents
Krishnaprasad holds a patent for a method and apparatus for training a learning model for automatic defect detection and classification of processed wafers. This patent, which is titled "Defect classification of processed wafers," involves receiving labeled images with defect classification types and features for portions of a post-processed wafer. The process includes creating a first training set from these images and training a machine learning model to classify wafer portions based on detected defects. Additionally, it incorporates labeled wafer profiles with downstream yield data to create a second training set, allowing the model to determine the respective downstream yield of a wafer.
Career Highlights
Krishnaprasad is currently employed at Applied Materials, Inc., a leading company in the field of materials engineering. His work focuses on advancing technologies that improve the manufacturing processes of semiconductors and other materials. His innovative contributions have positioned him as a key player in his field.
Collaborations
Some of his notable coworkers include Rahul Reddy Komatireddi and Rohith Cherikkallil. Their collaborative efforts contribute to the ongoing advancements in technology and innovation within their organization.
Conclusion
Krishnaprasad Reddy Mallavaram's work exemplifies the impact of innovation in the field of machine learning and semiconductor manufacturing. His patented methods are paving the way for more efficient defect detection and classification processes.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
