Data Science News

We are delighted to report that Dr Ramanujan Sridharan from the Theory and Foundations (FoCS) research theme at the Computer Science Department has received a prestigious EPSRC New Investigator Award. The approximately £264K project titled "New frontiers in Parameterizing Away From Triviality” aims to develop novel notions of graph edit distance and investigate their connections to efficient solvability of computationally hard problems.

the proposal identifies research questions that are novel, has the potential to have a broader impact both within and outside academia and it is an exciting project that will break new ground.

We're happy to announce that Zhenjian Lu has joined the department as a Research Fellow. He is currently funded by the project "New approaches to unconditional computational lower bounds", with support from the Royal Society.

Zhenjian Lu will soon defend a PhD thesis in computational complexity at Simon Fraser University under the supervision of Prof. Valentine Kabanets and Prof. Andrei Bulatov.

He is primarily interested in Computational Complexity, Circuit Lower Bounds, Algorithms, Pseudorandomness, Analysis of Boolean Functions, and Meta-Complexity.

Dr Theo Damoulas (Department of Computer Science) along with Dr David Armstrong (Department of Physics) and Jevgenij Gamper (Department of Mathematics) have developed probabilistic machine learning algorithms that can separate out real planets from fake ones in the large samples of thousands of candidates found by telescope missions such as NASA’s Kepler and TESS. The results of which have led to fifty new confirmed planets, the first to be not only ranked but also probabilistically validated by machine learning.

The paper "Exoplanet Validation with Machine Learning: 50 new validated Kepler planets" has been accepted to the Monthly Notice of the Royal Astronomical Society, DOI: 10.1093/mnras/staa2498