Head of Architecture at Lancaster and Chair of the National RIBA Practice and Policy Committee, Des’s field of research interest is in optimisation and Deep Learning (AI) for Decision Support Systems in design.  See: www.desfagan.co.uk 

He is particularly interested in the impact that Machine Learning will have on design processes and the regulatory and policy implications for the RIBA and ARB. 

In his current role as Chair at the RIBA, Des oversees the development of a programme of policy and public affairs activity to affect change in Whitehall, Westminster and beyond.

Prior to working in academia, he worked on several international award‐winning projects as Project Architect for the London Olympic Village for GHA and Glasgow Transport Museum for Zaha Hadid Architects, winner of European Museum of the Year. 

Des has published two books ‐ ‘UEM’ which reimagines the future of a sustainably eco‐centric City, and ‘Datascape’ – a collaborative research document which records the data activities and exchanges of a City.

Artificial Intelligence (AI) in Architecture Machine Learning (ML) for Architectural Design Social and Ethical Role of the Architect Explianability / Interpretability of AI in Architecture and Building Future Regulation of the Architect Decoding A.I for the Architect Parametric Architecture for Design Optimisation Software for Design Bioclimatic / Kinetic Facades Prototyping in Architecture Dataset Bias Architecture