Archive news content can be found here.
Best Student Paper Award at ITCS 2022
We are delighted to announce that Peter Kiss, a PhD student in the Theory and Foundations Research Division, has won the Best Student Paper Award at the Innovations in Theoretical Computer Science (ITCS) 2022 conference for his single-author paper on "Deterministic Dynamic Matching in Worst-Case Update Time". Computing a maximum matching in a graph is one of the most fundamental problems in design and analysis of algorithms. The paper makes important progress on this problem in a setting where the input graph is changing over time via a sequence updates, and one wishes to maintain a large matching efficiently in such a dynamic graph. Along the way, the paper develops a general purpose technique for converting any dynamic algorithm with amortised update time into one with worst-case update time, provided the initial algorithm is able to handle a more general form of batch updates.
Members of the High-Performance and Scientific Computing Group (HPSC) at the department of Computer Science has won a best paper award at the 28th IEEE International Conference on High-Performance Computing, Data and Analytics held on the 17th-18th of December. The winning paper titled Predictive Analysis of Large-Scale Coupled CFD Simulations with the CPX Mini-App, develops a novel representative (mini-)application, specifically designed to model coupled execution of multi-physics numerical simulation codes from the CFD domain. The mini-coupler, CPX, is the first of its kind, combining multiple CFD mini-app instances to predict the run-time and scaling behaviour of large scale coupled CFD simulations, on modern multi-core and many-core clusters such as used for production turbomachinery design at Rolls-Royce plc. The work was carried out by PhD candidate, Archie Powell, in collaboration with Kabir Choudry, Arun Prabhakar, and Gihan Mudalige at the Department of CS Warwick, Dario Amirante (University of Surrey), Istvan Reguly (PPCU) and Stephen Jarvis (University of Birmingham).
The work was funded by the EPSRC Prosperity Partnership in Computational Science for Advanced Simulation and Modelling of Engineering Systems (AsiMoV) and Rolls-Royce plc.
Dr. Gihan Mudalige at the University of Warwick’s Department of Computer Science have been awarded an Engineering and Physical Sciences Research Council (EPSRC) ExCALIBUR research grant as part of a consortium of researchers including the Science and Technologies Facilities Council (STFC), universities of Warwick, Newcastle, Cambridge, Southampton and led by Imperial College London.
This 3 year, £2.6M project brings together communities from the UK Turbulence Consortium (UKTC) and the UK Consortium on Turbulent Reacting Flows (UKCRF) to ensure a smooth transition to exascale computing, with the aim to develop transformative techniques for advancing their production simulation software ecosystems dedicated to the study of turbulent flows. It is part of the ExCALIBUR (Exascale Computing ALgorithms and Infrastructures Benefiting UK Research) programme, aimed at delivering the next generation of high-performance simulation software for the highest-priority fields in UK research.
A team of TIA researchers have published their study on a new deep learning algorithm that can pick up the molecular pathways and development of key mutations causing colorectal cancer more accurately than existing methods, meaning patients could benefit from targeted therapies with quicker turnaround times and at a lower cost. The research was funded by the UK Medical Research Council (MRC) and conducted in collaboration with colleagues at the UHCW NHS Trust, University of Nottingham and WHO IARC. The study has just been published in the prestigious Lancet Digital Health journal.
EPSRC funding awarded to Dr Ramanujan Sridharan and Professor Graham Cormode
We are delighted to report that Dr Ramanujan Sridharan (PI) from the Theory and Foundations (FoCS) research theme at the Department of Computer Science and Professor Graham Cormode (Co-I, affiliated with FoCS) have been awarded an EPSRC Standard Research Grant, "New Horizons in Multivariate Preprocessing (MULTIPROCESS)".
This 4-year £540K project aims to advance the theory of preprocessing by designing novel multivariate preprocessing algorithms and extending their scope to high-impact big data paradigms such as streaming algorithms.
We are delighted to report that Dr Long Tran-Thanh has received a AIJ Prominent Paper Award for his first-authored paper, Efficient crowdsourcing of unknown experts using bounded multi-armed bandits, published in 2014 at Artificial Intelligence (AIJ), a premier journal in the field of artificial intelligence. The AIJ Prominent Paper Award recognises outstanding papers published in the journal in the last seven years that are exceptional in their significance and impact.
The paper developed the first comprehensive framework for the rigorous and principled mathematical analysis of task allocation algorithms in crowdsourcing systems. In addition, the paper proposed bounded bandits, a new sequential decision making model to solve task allocation problems with resource constraints. The work has had a significant impact on subsequent work carried out in both industry and academia. The award will be presented at IJCAI 2021, a top tier international conference in artificial intelligence.
Professor Mike Paterson presented with a 2021 Paul Halmos - Lester Ford Award
The Mathematical Association of America has presented Mike Paterson with a 2021 Paul Halmos - Lester Ford Award for an article of "expository excellence published in The American Mathematical Monthly". There were several unusual aspects to this paper: the title, "A head-ache causing problem"; the authors, "Conway, J.H., Paterson, M.S., and Moscow, U.S.S.R"; the sole reference in the paper is to itself; the main result is first disproved and then proved; and the acknowledgments make clear that Conway wrote the paper. Paterson previously received this award in 2010 (then the Lester Ford Award) for his "Overhang" article. More information can be found here.