Eram is a Professor of Particle Physics at Queen Mary, University of London where he leads the ATLAS research group working on the Large Hadron Collider at CERN.
He is the Director of the EPSRC funded Centre for Doctoral Training in Data-Centric Engineering. As the Director of Training in the DISCnet CDT, he is responsible for delivering data science training to PhD students between the universities of Queen Mary, London, Sussex, Southampton, Portsmouth and the Open University.
He is currently the Deputy Dean for Research at Queen Mary, and holds an Associateship with the University of Durham in particle physics phenomenology.
Analysis of data from the Large Hadron Collider will benefit greatly from applications of data science and artificial intelligence algorithms. Eram will continue his research in three main areas in collaboration with Turing. The first is the application of advanced AI techniques to observe the very rare decay of the Higgs boson to muon and anti-muon pairs which is overwhelmed by large backgrounds. This decay not yet been seen and is the only possible test of Higgs couplings to second generation fermions. Secondly the upgrade of the LHC in 2021 will require rapid online selections to be made within microseconds before recording collision data to disk. The selections will be deployed in fast electronics as part of the trigger system for the ATLAS detector. Eram is interested in the implementation of AI methods to improve data efficiency. Finally he aims to perform precision measurements of the electroweak sector of the Standard Model in which novel AI methods can be used to unfold complex detector distortions from high precision data.