Accelerate Lunchtime Seminar Series
Starts: 2026/04/20 at 12:00
Ends: 2026/04/20 at 13:00
Join us to find out more about research taking place in AI for Science across the Accelerate Science community.
Details of future talks are available on Talks@Cam
Lunch provided, registration is required, please register here.
A Novel Diffusion Model based Approach for Sleep Music Generation
Kevin Monteiro, Department of Computer Science and Technology, University of Cambridge
Sleep disorders, particularly insomnia, and mental health conditions affect a significant fraction of adults worldwide, posing seriousmmental and physical health risk. Music therapy offers promising, low-cost, and non-invasive treatment, but current approaches rely heavily on expert-curated playlists, limiting scalability and personalisation. We propose a low-cost generative system leveraging recent advances in diffusion models to synthesize music for therapy. We focus on insomnia and curate a dataset of waveform sleep music to generate audio tailored to sleep. To ensure real-world feasibility, we optimize our system for training andmuse on a single GPU , balancing quality and efficiency through extensive ablation studies. We show through subjective human evaluations that our generated music matches or outperforms existing baselines in both perceived quality and relevance to sleep therapy, while using only a fraction of the computational cost.
Numerically verified proofs in pure maths
Daniel Platt, Department of Mathematics, Imperial College London
What’s a numerically verified proof? In pure maths we want to prove theorems, usually using pen and paper. On the other side there exist hundreds of very elaborate ways to approximately solve equations, for example physics-informed neural networks. Due to the advent of greater computational power it has recently become possible to use such approximate solutions in a theorem proofs. In the talk, I’ll explain how that works in a toy example and then briefly mention some applications of this in pure maths.
These seminars are open to members of the University of Cambridge. For further details, please email accelerate-science@cst.cam.ac.uk.