Anna is a Senior Lecturer in the School of Built Environment, Engineering and Computing. In the first 10+ years of her career, Anna worked in research and HE in the interpretation of data, analysis of the results and the application of machine learning and AI to be discovered from data. Her main area of research interests is in applied data science, sport, healthcare and computational toxicology. Anna also has experience of working in IT. She worked as a Software Developer in DBAM Systems Ltd (networking company) where she programmed embedded databases, software for TCP acceleration and worked on bandwidth usage optimization.

Tell us a bit about you and what led you to working in the School of Environment, Engineering and Computing

Although I’d always loved math, I ended up studying computer science subjects, and data analysis/signal processing were my favored modules. I gained my PhD in Computer Science at the University of Bradford, doing a funded industrial PhD in product safety. I’ve been working towards a model management system allowing aggregation and interpretation of predictive models used by Syngenta to assess the chemical toxicity. I then worked as Research Fellow at the University of Bradford for the EU project titled “Integrated In Silico Models for the Prediction of Human Repeated Dose Toxicity of Cosmetics to Optimise Safety” funded by EC FP7 and at the University of Leeds for an interdisciplinary project called Quanticode funded by EPSRC . This project involved health and social care data.

I started my job as Senior Lecturer at LBU in 2019 in the Computing subject area. I was attracted by the lovely Headingley campus and the opportunity to join a fantastic team on the MSc Data Science Course. Just after the start I got the opportunity to contribute toward the new curriculum development for a new BSc in Data Science, and started an internal collaboration with colleagues from other schools. One of these collaborations opens a door to the sport analytic world.

What makes you passionate about your work around sport analytics and why is it important?

Have you ever watched Moneyball with Brad Pitt? The movie is about how data analytics change the way baseball players are evaluated. I watched it 10 years ago and never thought I would stand on this path myself. Thanks to the development of the technologies and IoT, the amount of data that are collected on players, teams, training, games - this big data are used in various aspects.  It helps coaches make more insight-driven recruitment decisions (looking at the athlete performance and talented individuals), it helps to create better (winning) sporting strategies for individual athletes and teams, it can be used as a risk assessment tool to prevent non-contact injuries, and finally, it can help broadcasters create a better viewing experience. For us analysts, it is the fantastic world of data and all the work has the immediate reward as the application of the developed methodology or systems used by the professionals and broadcasters.

How is collaboration integral to your work, and what are one or two collaborations that have been most meaningful to you?

Data scientists/analysts have skills to deal with data but often they do not have data. We become collaborators for business and research projects to help other professionals discover insights from their data. At LBU I got an amazing opportunity to join Prof Ben Jones’ team from the School of Sport and work on joint PhD projects related to Rugby Super League. The main aim of these projects was to work towards data management systems for Super League data, classification of player movements, discovering unique athlete/team movement patterns and athlete/team performance evaluation.

Enhancing the sports industry by using advanced analytical tools, such as pattern mining or deep learning to develop methodologies and business intelligence systems, allowing efficient data analysis, is the ultimate goal of this project. Such tools and system will support the decision-making process for sports practitioners.

What achievements in this area have you been most proud of?

We have a great team of PhD students working towards the project aims. We have developed a framework for a data management system for Rugby League Data, a project done in collaboration with Catapult and the Rugby Football League. We worked to develop methodologies for discovering frequent players movement patterns and developed new pattern mining algorithms. We evaluated teams performance between competition levels based on the frequent movement patterns and finally, we looked for a model assessing team performance based on the expected possession values. 
It is real pleasure to observe how computing and sport students influence themselves to achieve their goals, how they complement each other and the great job that they do.

As a part of such collaboration, we also built in our school the IT infrastructure for data storage and computation power, to allow students to perform complex and time-consuming analysis. The GPUs environment will be extended by the High-Resolution Power Wall display.