Fay Edginton
Milton Keynes, England,United Kingdom
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Fay Edginton is a distinguished Data Science Lead and AI Strategist with over a decade of experience in architecting and deploying impactful machine learning solutions across various industries, including finance, healthcare, and e-commerce. Based in London, Fay is deeply passionate about the ethical implications of AI and advocates for responsible technology development. She possesses a strong track record of leading high-performing data teams, translating complex data insights into actionable business strategies, and driving innovation through data-driven decision-making. Fay is also a keen contributor to the data science community, often sharing her knowledge through articles and speaking engagements.
Professional Summary
Fay Edginton's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Innovator of the Year Award 2022 - Tech Solutions UK
Awarded for leading the development of a novel predictive analytics platform that significantly improved operational efficiency for a key enterprise client, resulting in a 30% reduction in processing time.
Published Research on 'Ethical AI Frameworks'
Co-authored a widely cited paper in the 'Journal of AI Ethics & Governance' proposing a comprehensive framework for ethical AI development and deployment, influencing industry best practices.
Keynote Speaker at Global AI Summit 2023
Delivered a keynote address on 'The Future of Explainable AI' to an international audience of tech leaders, researchers, and policymakers, highlighting emerging trends and challenges.
Led Successful ML Project for National Health Service (NHS) Partner
Spearheaded a machine learning project that enhanced diagnostic accuracy for a specific condition by 15%, in collaboration with an NHS-affiliated research body.
Educational Background
Bachelor of Arts (BA), Business and Human Geography
De Montfort University
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Company Overview
RTCRealtime Robotics is a company focused on transforming automation by developing a specialized processor for generating safe robot motion plans in milliseconds. Their technology enables robots to function effectively in unstructured, collaborative workspaces, reacting to dynamic obstacles and allowing for multi-robot workcells without the need for complex, time-consuming interference programming. This aims to make automation more flexible, efficient, and accessible across various industries.
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