Company Filing History:
Years Active: 2025
Title: Andrew Langworthy: Innovator in Machine Learning Security
Introduction
Andrew Langworthy is a notable inventor based in London, GB. He has made significant contributions to the field of machine learning, particularly in enhancing the security of classification models. His innovative approach addresses vulnerabilities that can be exploited through model inversion attacks.
Latest Patents
Langworthy holds a patent for a groundbreaking invention titled "Classification model evaluation." This patent describes a computer-implemented method, computer system, and computer program designed to determine the susceptibility of machine-learned classification models to model inversion attacks. The method involves obtaining a set of sample data from the classification model, training a replica of the model using this data, and evaluating its properties to measure susceptibility. This invention is crucial for improving the security and reliability of machine learning applications.
Career Highlights
Andrew Langworthy is currently employed at British Telecommunications Public Limited Company, where he applies his expertise in machine learning and data security. His work focuses on developing innovative solutions that enhance the robustness of classification models against potential attacks. With a strong background in technology and research, Langworthy continues to push the boundaries of what is possible in the field of artificial intelligence.
Collaborations
Langworthy collaborates with Dhanish Ashraf, working together to advance their research and development efforts in machine learning security. Their partnership exemplifies the importance of teamwork in driving innovation and addressing complex challenges in technology.
Conclusion
Andrew Langworthy is a pioneering inventor whose work in machine learning security is making a significant impact. His patent on classification model evaluation showcases his commitment to enhancing the safety and effectiveness of artificial intelligence systems.