Vancouver, Canada

Nathalie Rauschmayr

This inventor holds 1 USPTO granted patent. Top assignee: Amazon Technologies, Inc.. Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Nathalie Rauschmayr. Retrieved from https://idiyas.com/inventor/nathalie-rauschmayr

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Nathalie Rauschmayr: Innovator in Machine Learning Diagnostics

Introduction

Nathalie Rauschmayr is a prominent inventor based in Vancouver, Canada. She has made significant contributions to the field of machine learning, particularly in the area of automatic failure diagnosis and correction. Her innovative work is paving the way for more reliable machine learning models.

Latest Patents

Nathalie holds a patent for "Automatic failure diagnosis and correction in machine learning models." This patent focuses on identifying input data that may cause failures in trained machine learning models. By clustering model failures, she aims to determine various failure scenarios. The generated examples and truth labels can then be utilized to retrain the machine learning model, resulting in a corrected version.

Career Highlights

Nathalie is currently employed at Amazon Technologies, Inc., where she continues to develop her expertise in machine learning. Her work is instrumental in enhancing the reliability and efficiency of machine learning applications.

Collaborations

Throughout her career, Nathalie has collaborated with notable colleagues, including Krishnaram Kenthapadi and Dylan Slack. These partnerships have contributed to her innovative research and development efforts.

Conclusion

Nathalie Rauschmayr is a trailblazer in the field of machine learning, with her patent and work at Amazon Technologies, Inc. showcasing her commitment to innovation. Her contributions are vital for the advancement of technology in diagnosing and correcting machine learning failures.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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