Below is a list of projects on the go at the Data Science Institute. While most projects pertain to the life sciences, from asthma to multiple sclerosis to seizure prediction, we are interested in taking on even more projects, both life sciences related and not. Using the analysis from these projects, we are able to find ways to visualize and present these data in the GDO. Contact us for more information.
Managing Air for Green Inner Cities project has the aim to develop citites with no air pollution and no urban heat. They have plans to use advanced techniques for data assimilation, sensor optimization, and reduced order modelling for urban flow.
Check out the website here.
Deep Learning on Fused Brain
Deep Learning on Fused Brain and Heart Signals for Mental Disorder Detection
We are developing a patient-specific seizure prediction and detection system by investigating the use of fused brain and heart signals. It is a non-invasive patient-specific seizure detection/prediction system which utilizes features extracted from EEG and ECG signal. It consists of two main components: 0. Seizure detection system 0. Seizure prediction system
Check out the GitHub code here.
Social and Cultural Analytics Lab
The Social and Cultural Analytics (SOCA) Lab brings together Imperial College researchers, and friends from allied institutions, to discover how culture and society work. Our members are mathematicians, physicists, biologists, computer scientists and engineers. We're studying the evolution of music, the neurobiology of creativity, the dynamics of twitter networks, digital markets, online collaborations, the application of text mining to health and much else besides.
Data Assimilation Lab
The data assimilation (DA) laboratory will promote and lead scientific advances and technological innovations through data assimilation, sensitivity/uncertainty/error analysis, design optimization and control, and computational modelling, simulation and visualisation methodologies. Our vision is to provide leadership, in the UK and beyond, in data assimilation as a strategic resource for scientific education, research and inquiry.