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
Professor Ben MacArthur Director of AI for Science and Government, Deputy Programme Director for Health and Medical Sciences, and Turing Fellow
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
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)
Omics data generation and analysis group Developing rigorous and robust data science methods for curation, collection and computation of omic data sets
Analysis of networks What problems of mutual interest are there for researchers interested in network analysis?