Project OASIS

Optimal and robust Approaches for Sparse, Invariant and Subdata selection methods

The project explores techniques at the intersection of robust statistics, high-dimensional analysis, and computational efficiency.
The aim of the project is to optimise the dataset through smart subdata selection methods focused on three core pillars: robustness, variable reduction and efficiency.

Ditch the noise, find the needle, and simplify massive data in a fraction of the time.