About the Institute
The Data Science Institute is one of the six Global Institutes of Imperial College London, created to address some of the most important issues facing the world today.
From health inequalities and the dangers of global warming, to the opportunities created by big data and molecular engineering, these issues are often too big to be tackled by individual academics or even departments. Therefore the Global Institutes aim to bring together the talents of a wide variety of researchers. They are by their nature outward-facing, promoting collaboration with policy makers and businesses and providing independent scientific advice.
The Institute hosts researchers and students conducting their own academic research on a range of topics within the four crosscutting research themes of Analytics, Biomedical Informatics, Image Informatics, and Visualization.
The Institute works with academics across the College through its Academic Fellowship Programme, which provides networking opportunities and access to some DSI facilities .
If you are interested in working with the DSI, visit our Get Involved page.
Discover more about the DSI's long term plans: download our Strategy of DSI 2016-2021
Data science is at the core of all scientific activities, as it involves the whole life cycle of data, from acquisition and exploration to analysis and communication of the results. Data science is not only concerned with the tools and methods to obtain, manage and analyse data: it is also about extracting value from data and translating it from asset to product.
Launched on 1st April 2014, the Data Science Institute at Imperial College London aims to enhance Imperial's excellence in data-driven research across its faculties by fulfilling the following objectives.
- To act as a focal point for coordinating data science research at Imperial College through cross-disciplinary collaboration.
- To train and educate the new generation of data scientists.
- To develop data management and analysis technologies and services that support research.
- To translate data science into innovation collaborating with partners in industry and the public sector, and to support commercialisation.
- To promote data science and its applications outside academia and to influence policy makers.