Los Angeles, CA, United States of America

Mozhdeh Rouhsedaghat

This inventor holds 2 USPTO granted patents and 3 published patent applications. Top assignee: Paypal, Inc.. Active years: 2023-2026.

USPTO Granted Patents = 2 

% Patents Active = 100.0

Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2023-2026

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2 patents (USPTO):Explore Patents

Title: Innovator Mozhdeh Rouhsedaghat: Pioneering Machine Learning Vulnerability Identification

Introduction

Mozhdeh Rouhsedaghat is an accomplished inventor based in Los Angeles, CA. She has made significant contributions to the field of machine learning, particularly in the area of vulnerability identification and retraining. Her innovative work aims to enhance the robustness of machine learning models against adversarial attacks.

Latest Patents

Mozhdeh holds a patent for an "Automatic machine learning vulnerability identification and retraining." This patent discloses techniques for training machine learning models to effectively handle adversarial attacks. The process involves perturbing a set of training examples using various adversarial attack methods. The computer system identifies a set of sparse perturbed training examples that can be used to train models to recognize adversarial attacks. This approach ensures that the machine learning model can correctly classify data associated with such attacks.

Career Highlights

Currently, Mozhdeh is employed at PayPal, Inc., where she continues to develop her expertise in machine learning and artificial intelligence. Her work at PayPal allows her to apply her innovative ideas in a practical setting, contributing to the company's advancements in technology.

Collaborations

Mozhdeh collaborates with Nitin S Sharma, leveraging their combined expertise to push the boundaries of machine learning research and application.

Conclusion

Mozhdeh Rouhsedaghat is a trailblazer in the field of machine learning, with her patent on vulnerability identification showcasing her innovative spirit. Her contributions are paving the way for more secure and resilient machine learning systems.

Profile summary based on public USPTO records.
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