: Paper accepted for 32nd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2022), Xi'an, China, 22-:.27 Jun - : Interviewed by Tech Monitor (27 Jun) and BBC Tech Tent (1 Jul) on virtual reality sound.
: Dr Emily Corrigan-Kavanagh co-organizing in-person "Designing AI for Home Wellbeing" World Cafe at the Design Research Society conference DRS 2022 Bilbao (25 Jun - 3 Jul). 11 Jul: "Designing AI for Home Wellbeing" World Cafe, supported by the University of Surrey Institute of Advanced Studies. 12 Jul: "Designing AI for Home Wellbeing" Seminar Day, supported by the Surrey Institute for People-Centred AI. 11-: At two-day face-to-face workshop on "Designing AI for Home Wellbeing". 17-: Attending (virtually) 39th International Conference on Machine Learning (ICML 2022). Plumbley and Tuomas Virtanen) Session: MON9.1/d - Advances in Environmental Noise (14:40-17:00) 22 Aug: Presenting our paper: Creating a new research community on detection and classification of acoustic scenes and events: Lessons from the first ten years of DCASE challenges and workshops (Mark D. 21-: See you at 51st International Congress and Exposition on Noise Control Engineering (Inter-noise 2022), Glasgow, Scotland. For examples of potential projects and funding opportunities, see Supervision. I welcome applications from excellent students who wish to study for a PhD in my areas of research interest. I was co-Chair of the DCASE 2018 Workshop on Detection and Classification of Acoustic Scenes and Events, co-Chair of the 14th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2018) and co-Chair of the Signal Processing with Adaptive Sparse Structured Representations (SPARS 2017) workshop. 
My total grant funding is around £54M, including £20M as Principal Investigator, Coordinator or Lead Applicant. I currently hold an EPSRC Fellowship on "AI for Sound", and recently led EPSRC projects Making Sense of Sounds and Musical Audio Repurposing using Source Separation, and two EU research training networks, SpaRTaN and MacSeNet. Much of my research is funded by grants from EPSRC and EU, Innovate UK and other sources. I have published over 400 papers in journals, conferences and books, including over 70 journal papers and the recent Springer co-edited book on Computational Analysis of Sound Scenes and Events. My focus is on detection, classification and separation of acoustic scenes and events, particularly real-world sounds, using methods such as deep learning, sparse representations and probabilistic models. My research concerns AI for Sound: using machine learning and signal processing for analysis and recognition of sounds.
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