Dr Niall Jeffrey is an AI+ Academic Senior Fellow in the Department of Physics. He is a cosmologist and machine learning researcher whose work sits at the intersection of physics, statistics, and artificial intelligence. He collaborates with major international projects including the Dark Energy Survey (DES), DESI, and Euclid, developing advanced statistical methods to better understand dark matter, dark energy, and the evolution of the Universe. Alongside his academic research, Niall is active in science communication and media outreach, having written for The Times and appeared on TV and radio. He is also the co-founder of an AI startup using machine learning to tackle real-world sustainability challenges.

Awards

• Royal Astronomical Society Early Career Award 2025
• (Finalist) Dr Katharine Giles Award for best popular article written by a scientist or engineer 2024
• ABSW Media Fellow 2023
• Jacky Pallas Memorial Award 2021

Research 

AI for physics

Scientific inference problems are very different from many applications of machine learning and artificial intelligence. Problems are often data-scarce and we need a good understanding of our uncertainty to make scientific conclusions.

Cosmological inference

There is a lot we do not understand about the Universe: dark matter, dark energy, neutrinos, and the details of cosmic inflation. We are also faced with apparent tensions between observations at different cosmological times. I use novel statistical techniques to answer these questions using data from galaxy surveys.

Additional Information

Niall Jeffrey 

Publications