Professor Mark PlumbleyPrincipal Investigator
My research concerns AI for Sound: using machine learning and signal processing for analysis and recognition of sounds. 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.
Dr Helen CooperProject Officer and Facilities Manager
Within CVSSP, I am responsible for the day to day management of research projects, as well as coordinating the lab facilities and ensuring that the researchers have the equipment and tools they need to do their research.
Dr Emily Corrigan-KavanaghResearch Fellow in Design Research
I am a design researcher, practitioner and academic, with special interests in happiness, wellbeing, service design, home, visual communication, design for augmented paper, art therapy techniques, creative research methods, and exploring/making sense of subjective experiences.
Dr Arshdeep SinghResearch Fellow in Machine Learning for Sound
My research focuses on designing low computational complexity learning-based frameworks for audio classification. My research interest includes signal processing, audio scene analysis, dictionary learning, machine learning and compression of neural networks for efficient inference.
Gabriel BibbóResearch Engineer
With my background in electronics and signal processing, I work at the intersection between development and production, focusing on software and hardware solutions for research problems related to sound and AI.
Haohe LiuPhD Student
The goal of my research is to develop new methods for automatic labeling of sound environments and events in broadcast audio, assisting production staff to find and search through content, and helping the general public access archive content. I’m also working closely with BBC R&D Audio Team on putting our audio recognition algorithms into production, such as incorporating machine labels into the BBC sound effect library.
James KingPhD Student
I focus on AutoML (Automated Machine Learning), information-theoretic machine learning, Graph theory and their applications to audio. My research focuses on developing novel algorithms for analysing soundscapes using techniques from machine listening and spatial audio. I strive to create efficient methods that can be used by both academic researchers and industry professionals for automated problem-solving in challenging acoustic environments.
Andres FernandezResearch Engineer
With my background in computer science and music, I work at the intersection between development and production, focusing on software solutions for research problems related to sound and AI.
Dr Marc GreenResearch Fellow in Machine Learning for Sound
My research is focused on environmental soundscapes, with a view to utilising techniques from machine listening and spatial audio in their analysis.
Dr Yin CaoReserch Fellow
Research on audio signal processing, acoustics, audio and speech signal processing.