Inaugural Paul Brooks Prize Awarded

We are delighted to announce that the winner of the inaugural Paul Brooks Prize at St Catherine’s College, Oxford, is Lorenzo Piersante with an award of £500. The Paul Brooks Prize is awarded annually to a Physics student to recognise and support aptitude and achievement in practical applications of science and technology.

Commenting on his win and his project titled ‘A Machine Learning model for the Atomic Structure Determination of molecules in Atomic Force Microscopy images’, Lorenzo said:

‘I was really happy of the fact that the audience and the jury appreciated that machine learning (ML) and artificial intelligence (AI) can be helpful tools not just for data analysis purposes but also as means to automate experimental procedures that can be extremely tedious and time-consuming.

I wanted to show how modern computational methods can be applied to solve problems of relevance in Physics and beyond. I especially wished to convey the fact that the development of computational tools is an area of research in its own right. In other words, computational simulations, when not treated as black boxes, can become incredibly powerful tools to gain a better understanding of physical systems.

Atomic Force Microscopy (AFM) has emerged as an extraordinary technique to directly probe the structure and properties of molecules. Despite the great promise, the difficulties associated with fine tuning the experimental equipment and interpreting the images of some molecules have limited its wide-spread use. Then, the project I worked on aimed to optimise a computational tool for the analysis of AFM images.

This software package is based on a combination of image processing and graph reconstruction techniques implemented through artificial intelligence methods. In perspective, such tools will aid surface scientists in both analysing AFM images and automating the data-taking process.’

Two runner-up prizes were also awarded with an award of £250:

  • Yang Hu for his project titled ‘Constraining Spatial Curvature with Strong Gravitational Lenses and Complementary Probes: a Forecast for Next-Generation Surveys’
  • Magdelana Stenfors for her project titled ‘Detecting Insider Trading with Deep Learning; Predicting Stock Price Movement from News Headlines’

Congratulations to all the winners and many thanks to Paul Brooks for supporting this award. Applications for the award will reopen in the next academic year.

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