Fundamentals of AI University of Oxford

Overview

The Fundamentals of AI programme offered by University of Oxford is dedicated to advancing foundational research in artificial intelligence and machine learning, focusing on theoretical underpinnings and methodological innovation. The CDT's aim is to develop AI technologies with the potential to drive transformative impact across key global challenges aligned with the missions of Ellison Institute of Technology.

Features 

• Theory and Foundations: Researchers in this area focus on the foundational mathematical, statistical, and computational principles that underpin AI. This includes research in topics such as learning theory, optimisation, stochastic analysis, complexity theory and formal methods. The aim is to create formal frameworks for the analysis of AI algorithms and systems in order to gain insight into properties, understand behaviours and to develop improved algorithms that could have widespread general use in the field.
• Applied Fundamentals: At the FoAI CDT, researchers maybe interested in particular applications of AI relevant to EIT’s Humane Themes and Scientific Programmes. Researchers in this area will examine how scientific challenges and the properties of real-world data can guide the reformulation of existing AI algorithms or the design of new algorithms entirely. Topics in this area include physical and process modelling, how to handle missing data, multimodal data integration, decision support, etc.
• Fundamentals of AI Systems and Engineering: In recent years, there has been an unprecedented emergence of large and complex AI systems, such as Large Language Models. Researchers in this area are interested in the formal frameworks for characterising the design and development of such systems and using these to further understand the properties and behaviours of such systems. They may also be interested in the security, scalability and physical resource requirements of such systems.