Dr Sam Jackson

Assistant Professor in the Department of Mathematical Sciences

What do you do?

I'm an Assistant Professor of Statistics, my research and teaching specialises in the areas of computer modelling of physical systems, uncertainty quantification, risk management, decision support and machine learning. When not doing Statistics, I love playing the organ, playing tennis and bouldering.

How are you involved in this area of science? 

I carry out Uncertainty Quantification of the major sources of uncertainty in computer models and their links to corresponding physical systems utilising a Bayesian statistical framework. This in turn permits appropriate propagation of uncertainty through any statistical analysis to decision making, thus making sure uncertainty is mitigated as best possible, or otherwise taken into account, when choices are made that affect all of our lives.

Often, the computer models themselves are intensively complex and take a long time (hours, days, months) at one input setting. Consequently, we construct statistical approximations, known as emulators, to approximate model behaviour for any input setting, along with a corresponding uncertainty estimate. I thus carry out efficient inference across a wide range of application areas including defence threat reduction, epidemiology, medical imaging and systems biology.

What do you love about this topic?

I love the fact that utilising Bayesian statistics for Uncertainty Quantification is liberating in that we can use all sources of information, including expert judgement and knowledge, in conjunction with data, whilst confronting all sources of uncertainty that may otherwise cloud our judgement when making decisions. I love the diversity of application areas that I get to work on as a result, and the fact that a meaningful uncertainty quantification permits confident decisions that can have real-world impactful benefit for humankind.

How does this work deliver real-world impact?

Real world impact is achieved in all of our applications, for example:

• Medical imaging - permitting clearer X-ray images to be produced at cheaper cost and with reduced harmful dose to patients.
• Systems biology - understanding genetic mutation of agricultural crops for life sustainability amidst an evermore hostile climate environment.
• Epidemiology - make predictions about the spread of infectious diseases, such as COVID-19 under different intervention scenarios, and thus aid confident policy making, particularly on a local level.