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Energy

Interdisciplinary Research Centre
 
Date: 
Friday, 27 March, 2026 - 09:00 to 17:45
Event location: 
Online and Engineering Department

Overview

Professor Sir David MacKay (1967-2016) made fundamental contributions to both public and theoretical understandings of energy and of information. He served as Chief Scientific Adviser to the Department of Energy and Climate Change and was Professor of Natural Philosophy in the Cavendish Laboratory before being appointed as the inaugural Regius Professor of Engineering. He was a Fellow of Darwin College. 

This one-day meeting of the Cambridge Philosophical Society, dedicated to his memory, considers both the urgent challenges of sustainable energy resources and the global opportunities arising from information technologies. We will be addressing the two main themes of his work: machine learning, information theory and Bayesian inference, together with sustainable energy. The meeting marks the tenth anniversary of David’s death, with speakers who worked with David, build on his contributions in the field of energy and information, and share his values on the importance of clear and accessible communication.

The meeting in Cambridge University Engineering Department is open to all to attend, without charge. The lectures will be live-streamed; edited recordings will later be made available through the Cambridge Philosophical Society website. 

Registration for both in-person and virtual attendance is recommended and will open in December.

Register: David MacKay: Energy and Information | Cambridge Philosophical Society

Program

 

09.00

Welcome, introduction.

David in Cambridge.

Professor Deborah Prentice (Vice Chancellor), Dr Claire Barlow and others

Personal and family perspectives

Prof Robert MacKay

Science and policy

Dr Rob Doubleday

 

Tea/coffee

 

Synthesising data-based approaches to climate change

Prof Emily Shuckburgh

David at DECC: Impact and legacy.

Moira Wallace, Ravi Gurumurthy

12.45-14.00

Lunch break

 

Bayesian science

Prof Steve Gull

Machine learning and ethics

Dr Hanna Wallach

 

Tea/coffee

 

Probabilistic AI in 2026

Prof Zoubin Gharamani

Information, Energy and Intelligence

Prof Neil Lawrence

 

Closing remarks

Prof Alan Blackwell

17.45

Meeting ends