This event celebrated the launch of an exciting new research Institute which is a collaboration between the Cantab Capital Partners LLP and the University of Cambridge. Hosted within the Faculty of Mathematics of the University of Cambridge, the Cantab Capital Institute for the Mathematics of Information will push the boundaries of information science.
Established through philanthropic support of £5 million from Cantab Capital Partners, the Institute will accommodate research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute will be on the highest international level, aiming to extract the relevant information from large-and high-dimensional data with a predictable certainty.
At the heart of the Institute, will be the fundamental mathematical techniques and their intra-disciplinary engagement, upon which, the solution of big data questions so heavily relies. This is crucial in order to ensure advancements in data science.
Photo credit: Chris Loades
This launch event provided an opportunity to learn more about the work of the Institute, such as the specific questions that feed into fundamental methodology development. It is anticipated that the research will focus on various applications across a number of interdisciplinary engagements. These could include for instance, economists and social scientists on questions about financial markets and the internet, or with physicists and engineers on software and hardware development questions in the context of security.
Presentations at the event introduced areas of mathematical expertise represented in the Institute and outline how fundamental techniques can be drawn on to meet the challenge of deciphering meaning in the ever growing volumes of data. Academic expertise at the Institute includes:
The highlight of the launch was the inaugural lecture of the Institute given by Professor Ronald DeVore from Texas A&M University. Ron is one of the key figures of modern applied mathematics and made substantial contributions to approximation theory, numerical analysis of partial differential equations, wavelet transforms, machine learning algorithms and the theory of compressive sensing.
Photo credit: http://chrisloades.webs.com
This event also presented a great opportunity for participants to network with senior scientists and relevant individuals from end user communities. The afternoon finished with drinks and a networking reception.
View more images from the launch here.