Advancing methodology for predictive healthcare Developing methodologies for complex health data and individual-level risk prediction
Uncertainty quantification of multi-scale and multi-physics computer models Developing new tools to investigate and quantify uncertainties in computer models, with applications to climate, earthquake and tsunami models
Data-driven experiment design Developing new statistical tools to select the most informative biological laboratory experiments to perform, to maximise learning and minimise research costs
Probabilistic Value-Deviation-Bounded Integer Codes for Approximate Communication When computing systems can tolerate the effects of errors or erasures in their communicated... Stanley-Marbell, Phillip, and Paul Hurley. "Probabilistic value-deviation-bounded integer codes for approximate communication." arXiv preprint arXiv:1804.02317 (2018)
Statistics and computation Monday 13 Jan 2020 - Tuesday 14 Jan 2020 Time: 10:00 - 17:00 Carola-Bibiane Schönlieb Caroline Uhler Florent Krzakala Francis Bach Garvesh Raskutti Jean-Philippe Vert Lorenzo Rosasco Madeleine Udell Peter Bartlett Rebecca Willett Tamara Broderick Vitaly Feldman
Information-Theoretic Foundations and Algorithms for Large-Scale Data Inference Thursday 17 Dec 2015 Time: 17:37
Omics data generation and analysis group Developing rigorous and robust data science methods for curation, collection and computation of omic data sets