Declaration I, Richard Spinney, confirm that the work presented in this thesis is my own. The research carried out under this theme covers the development of generic stochastic models and the investigation of their properties, as well as modelling and inference for applications in a range of physical, biological and financial sciences. We would like to show you a description here but the site won’t allow us. Stochastic (from Greek στόχος (stókhos) 'aim, guess') is any randomly determined process. Lists linked to STAT0009: Stochastic Systems. climate and tsunami models); modeling in finance, econometrics, biostatistics; theoretical research on epidemic models and genetics, leading to applications in the life sciences and insight on biological mechanisms; 2019-2023: PI Guillas, EU COST action "Accelerating Global science In Tsunami HAzard and Risk analysis" (AGITHAR), UK representative and Chair of Working group on Uncertainties. Alan Turing Institute, in collaboration with the Universities of Oxford, Warwick and Exeter. Value: 1) 4,000 GPU-hours on the National GPU facility for Machine Learning, Molecular Dynamics, and Data Science Research JADE; 2) 46,000 GPU-hours & 41,000 KNL-hours on Cambridge Service for Data Driven Discovery (CSD3). Further details are available in the STAT0009 UCL Module Catalogue entry. Rouba’s research interests lie in stochastic modelling applications to service systems, especially call centers and healthcare systems. Probability, Uncertainty and Risk in the Natural Environment, £683k, NERC, University College London, Gower Street, London, WC1E 6BT Tel: +44 (0) 20 7679 2000. Value: £198k (100% FEC). Principally my work develops statistical techniques to deal with large, stochastic systems. Back to STATS_MAP: Statistical Science. Knowledge Transfer Partnership: Combination of Earthquake and Tsunami Catastrophe Models, £173k, EPSRC & NERC (50%) and Aspen Insurance Ltd (50%), Nov 2014 - Oct 2016, PI: Guillas. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. UCL Systems Biology; Vision Network; See More See Less Research Summary . 2018-2020 PI Guillas, "Uncertainty Quantification Of Multi-scale And Multi-physics Computer Models: Applications To Hazard And Climate Models". Value: £480,509. In particular, she is interested in applying queueing-theoretic methods and numerical tools, such as simulation modelling and data analysis, to problems relating to the operational management of service systems. modeling and inference for spatial-temporal processes, with important applications in environmental sciences including hydrology, climatology, and atmospheric science; modeling and inference for complex computer models (e.g. The Use of Stochastic Methods to Explore the Thermal Equilibrium Distribution and Define Entropy Production out of Equilibrium A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Doctor of Philosophy Department of Physics and Astronomy Faculty of Mathematical and Physical Sciences UCL Author: Richard Edward Spinney Stochastic Modelling of Complex Systems research covers the development of generic stochastic models and the investigation of their properties, as well as modelling and inference for applications in a range of physical and biological sciences. Value (without overheads): £23,123. 2017-2018 PI Guillas, NERC/AHRC/ESRCGlobal Challenges Research Fund (GCRF). Lists linked to STAT0009: Stochastic Systems. The Applied Analysis group at UCL Mathematics has a broad range of research interests in asymptotic-, functional-, complex- and stochastic analysis. Major components include: Hidden Markov Models; Financial Models; Econometrics; Inverse Problems; Graphical Models; Data Assimilation; Biostatistics; Copulas, Gaussian Processes; Inference for Stochastic Models; Statistical Emulators, Climatology; Hydrology; Inference for Stochastic Models; Multimodel Ensembles; Space-Time Modelling; Statistical Downscaling; Trend Analysis; Uncertainty Analysis, Hidden Markov Models; Volatility Time Series Models, Emulation and Calibration of Computer Models; Functional Data Analysis; Time Series; Tsunami Modelling, Energy Economics; Spatio-Temporal Modelling, Climatology; Hydrology; Inference for Stochastic Models; Modelling of Extreme Values; Multimodel Ensembles; Offshore Engineering; Rainfall Modelling, Stochastic Functional Differential Equations and Applications, Applications of Probability and Stochastic Processes to Problems in Genetics; Epidemic Models.