Welcome to The Centre for Fundamentals of AI and Computational Theory

Advancing the understanding and engineering of software and deep learning through mathematics, logic, and experimental science

AI and Deep Learning now permeate many aspects of our modern lives, alongside more conventional computational solutions to society’s needs and aspirations. That’s why it has never been more important to understand how AI and Computer Science work, in order to build them better and cheaper. To do this requires mathematical tools, engineering methodology and scientific method: these lie at the heart of what we do in FACT, the Centre for Fundamental AI and Computational Theory. 

Members of the centre apply Mathematics, Logic and experimental process to advance the theory and practice of software systems and deep learning, driving greater rigour and innovation in computation.

Our multi-disciplinary team includes expertise in: formal logic, information theory, topology, random matrix theory, computational neuroscience, natural language processing, signal processing and time series analysis. Thanks to our strong ties to application-oriented Centres at QMUL, we ground our research in meaningful applications, making our work significant and impactful.