Professor in the Machine Learning Group of the Computational and Biological Learning Lab in the Division of Information Engineering at the Department of Engineering in Cambridge Computational and Biological Engineering – Cambridge
Statistics, Uncertainty Quantification, Computer experiments, Multi-fidelity computer codes, Gaussian process regression, Kriging, Co-kriging, Sensitivity analysis, Design of experiments, meta-modelling
R E S E A R C H
Bayesian statistics, treatment of uncertainties and risk in industrial and ecological resource management Research Gate Linkedin
Home page – Mascott-Num JOURNAL ARTICLES A review on global sensitivity analysis methods Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes Metamodeling with Gaussian processes – slides Metamodeling with Gaussian processes : references Chilès & Delfiner, Geostatistics, Wiley, 1999 Fang, Li & Sudjianto, Design and modeling for computer experiments, Chapman, 2006 … Read more
Home page Research interests Gaussian process modeling Covariance function estimation Uncertainty quantification for computer experiments Small-probability estimation Confidence intervals post-model-selection Ph.D thesis : Parametric estimation of covariance function in Gaussian-process based Kriging models. Application to uncertainty quantification for computer models
Columbia University
Researcher at the Centre for Computational Biology (CBIO) of Mines ParisTech, Institut Curie and INSERM Machine learning for therapeutic research
School of Informatics, University of Edinburgh Teaching by Iain Murray Introduction to Machine Learning – video Publications by Iain Murray MLPR class notes Iain Murray’s other webpages and links Machine Learning – University of Edinburgh Iain Murray’s articles on arXiv
Gatsby Computational Neuroscience Unit Ed Snelson’s Publications