Adam Deedman (MSc Sound and Music Computing, 2024)
'Both of the jobs I have worked in since graduating have leaned heavily into the skills I learnt on the MSc Sound and Music Computing course. Particularly, utilising skills I honed in the development and inference of a variety of audio-to-audio AI models and familiarity with audio processing.'
Why did you choose to study your programme?
I wanted to specialise in AI for Music and Audio and the MSc Sound and Music Computing course seemed like the perfect option. Having not come from a traditional Computer Science background, it offered a good mix of fundamental AI/ML skills and more specialised courses on Audio and Music, taught by leading researchers.
Why did you choose to study at Queen Mary?
For Music and AI, Queen Mary and the C4DM is a world-leader. I read many papers from researchers at Queen Mary and wanted to be immersed in cutting-edge research within the department.
What did you most enjoy about your course?
I enjoyed learning many new skills and challenging myself every day. I loved being immersed in cutting-edge technology and research and being able to complete many exciting projects.
Can you share an example of a project, assignment, or activity that stood out to you?
I particularly enjoyed my Master’s project on the Evolution of British Folk Music using Graph Neural Networks. It was a very interesting project, in a novel research area and I learnt a lot during the process. I was also encouraged by my supervisor to submit the project to the EVOMUSART conference and I was able to travel to Italy to present my research, which was an amazing experience.
Which modules did you enjoy the most and were there any academics that had a strong influence on shaping your time and studies here?
I particularly enjoyed the modules on Deep Learning for Audio and Music, Music Informatics and Computational Creativity. All of these allowed us to explore fascinating techniques in Music and Audio AI, with really enjoyable, yet challenging projects. Johan Pauwels, Simon Dixon and Mathieu Barthet really helped shape my studies in a variety of ways and they are all leading researchers in their fields.
Describe your career path since graduating.
Since graduating, I spent a year working as a Junior AI Engineer for a startup called ‘SymphoMe’. We were building an AI-powered Piano Tutor and I got to contribute significantly towards the project, along with travelling to expos in Shanghai and San Diego.
Since December 2025, I have been working as a Junior Machine Learning Researcher at IRIS Audio, based in Central London. I have been predominantly working on developing cutting-edge speech enhancement models, which has been incredibly interesting.
How has your degree remained relevant throughout your career and are there any particular areas of your degree that you use in your day-to-day job?
Both of the jobs I have worked in since graduating have leaned heavily into the skills I learnt on the MSc Sound and Music Computing course. Particularly, utilising skills I honed in the development and inference of a variety of audio-to-audio AI models and familiarity with audio processing.
What’s one piece of advice you’d offer to someone considering studying your programme at Queen Mary?
Throw yourself completely into the experience, ask lots of questions and attend any workshops/labs/events the course offers. This is a unique opportunity to be able to learn from some of the leading researchers in Audio, Music and AI.