Innovative Machine Learning to Constrain Aerosol-Cloud Climate Impact
This research project – a collaboration between data scientists and climate scientists – will develop machine learning solutions to the analysis of the exploding amounts of climate data in order to deliver breakthroughs in climate research, whilst training the next generation of scientists.
Art Through the ICT Lens
This research project develops signal processing, image processing, and machine learning technology ingesting multi-dimensional datasets acquired on paintings to unveil distributions of materials within artwork.
Multi-Modal Signal Processing for Art Investigation
This research project develops machine learning technology ingesting multi-dimensional datasets acquired on paintings to reveal features of interest within paintings such as underdrawings, pentimenti, or concealed designs.
Information-Theoretic Foundations of Deep Learning
This research project explores the information-theoretic foundations of deep learning systems, including architectures, algorithms, and generalization bounds for supervised and semi-supervised deep learning approaches.
Learning to Communicate
This research project develops physical-layer technology based on deep learning solutions applicable to machine type communications.
Learning Privacy for the Internet of Visual Things
This research project develops privacy enhancing technologies for visual data based on deep learning solutions with applications to internet of things systems.
Machine Learning Through an Information-Theoretic Lens: From Deep-Learning to Meta-Learning
This research project explores the information-theoretic foundations of machine learning systems, with a special emphasis on emerging approaches such as transfer learning, continuous learning, and meta-learning.
Learning Privacy for the Internet of Moving Things
his research project develops privacy enhancing technologies for video data with applications to security and beyond.