Cavan Aulton: Optimising the Use of Machine Learning and Computer Vision in Sport
Having completed both his undergraduate and postgraduate degrees in Sport and Exercise Science at Sheffield Hallam University, Cavan is now following his passions and is researching the use of machine learning and computer vision in sports.
What is your PhD research focused on?
Optimising the use of machine learning and computer vision in sport from an ecological dynamics perspective. I want to promote an ecological framework that guides collaboration between practitioners and improves the design of machine learning and computer vision technology within athlete development programs to improve the skill development of athletes.
Why is it an important area of study?
Machine learning and computer vision are rapidly growing areas of research in sports but current approaches to their integration can result in ‘siloed working’ leading to sporadic approaches to athlete development. Currently, there has been no attempt to rationalise the application of machine learning and computer vision in sports. Providing practitioners with a framework to support the application of machine learning and computer vision can improve the use of these technologies within athlete development programs leading to improved performance.
Tell us about your career/academic journey so far
I’ve been at SHU since 2018 where I started as an undergraduate in the Sports and Exercise Science Course where my primary focus was on performance analysis. During this time, I completed an internship with the Sheffield Stealers Ice Hockey team where I went onto work until the end of 2021/22. After my Undergraduate, I stayed at SHU and studied Applied Sports and Exercise Science MSc from which I graduated in 2022 my primary focus was using R for performance analysis in football. During this time, I developed a keen interest in skill acquisition and ecological dynamics. I then started the graduate teaching assistant program in October 2022 at SHU. I currently work as a freelance analyst in ice hockey for teams in Europe and North America.
Why did you choose to study with the AWRC/SHU?
My interest in skill acquisition and ecological dynamics led me to talk to a lot of staff at SHU about this topic. I then realised that the skill acquisition group and sports engineering groups at SHU are world-leading in their respective fields, and both could benefit me highly in my research area. Also spending all of my academic time at SHU I have developed a lot of friends and made some great connections with the staff at SHU and I wanted to further develop these during my PhD. Dr Joe Stone and Dr Ben Stafford would also be very helpful in answering questions I had about a career in academia and the benefits of working at SHU on the Graduate Teaching Assistant scheme. Finally, the AWRC facility is cutting-edge and I really want to conduct my research there.
What’s it like being a PhD colocator at the AWRC? What do you enjoy most?
I really enjoy being a PhD student at the AWRC as mostly I’m not treated as a student and treated more as a member of staff which was always a concern as I am quite young. All the other staff members are kind and always take their time to speak with me and make me feel welcome, my ideas are valued and it’s a great place to work and collaborate on a different project with other researchers. It’s also really nice to be able speak to lots of interested people about your research!
What do you hope to do after your PhD?
I hope to pursue a career in academia focused on the applications of machine learning and computer vision in sports, I hope to stay involved in teaching in some way as I really enjoy being face-to-face with students, but my main passion is research.
Many thanks for speaking to us, Cavan, we wish you the best of luck with your studies!
Follow Cavan on Twitter.