Thanasis Pittas (Computer Science), advised by Ilias Diakonikolas (Computer Science) is working on robust statistics. His aim is to design efficient algorithms that can tolerate a constant fraction of the data being corrupted. The significance of computational efficiency arises from the high-dimensional nature of datasets in modern applications. To complete our theoretical understanding, it is also imperative to study the inherent trade-offs between computational efficiency and statistical performance of these algorithms.
