About The Institute

The advance of data science and the solution of big data questions heavily relies on fundamental mathematical techniques and in particular, their intra-disciplinary engagement. This is at the heart of the Institute, involving mathematical expertise ranging from statistics, applied and computational analysis, to topology and discrete geometry – all with the common goal of advancing data science questions.

It accommodates research activity on fundamental mathematical problems and methodology for understanding, analyzing, processing and simulating data.

On the other hand, specific questions that feed into fundamental methodology development will arise naturally in applications we focus on in interdisciplinary engagements with, for instance, economists and social scientists on questions about financial markets and the internet, with physicists and engineers on software and hardware development questions in the context of security, imaging and structured data processing, as well as biomedical scientists on data science in healthcare and biology.

Key mathematical expertise represented in the institute includes statistics; pure, applied and computational analysis; inverse problems; stochastic analysis and probability; convex analysis; stochastic and sparse optimisation; sparsity, compressed sensing and sampling theory; random matrices; harmonic analysis; partial differential equations; functional analysis; discrete geometry; number theory; topology and graph theory; quantum computing, cryptography and communication.

The below interview with CCIMI Director Carola Schönlieb is courtesy of Plus Magazine, and links with an article Carola authored discussing the Institute and the Mathematics of Information