Statistical Science


Stochastic Modelling of Complex Systems

Theme Overview

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. Major components include:

  • 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. 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;

Theme members

Alexandros Beskos (Theme Lead)Hidden Markov Models; Financial Models; Econometrics; Inverse Problems; Graphical Models; Data Assimilation; Biostatistics; Copulas
Francois-Xavier BriolGaussian Processes; Inference for Stochastic Models; Statistical Emulators
Richard ChandlerClimatology; Hydrology; Inference for Stochastic Models; Multimodel Ensembles; Space-Time Modelling; Statistical Downscaling; Trend Analysis; Uncertainty Analysis
Petros DellaportasHidden Markov Models; Volatility Time Series Models
Serge GuillasEmulation and Calibration of Computer Models; Functional Data Analysis; Time Series; Tsunami Modelling
Giampiero MarraEnergy Economics; Spatio-Temporal Modelling
Paul NorthropClimatology; Hydrology; Inference for Stochastic Models; Modelling of Extreme Values; Multimodel Ensembles; Offshore Engineering; Rainfall Modelling
Matina RassiasStochastic Functional Differential Equations and Applications
Afzal SiddiquiEnergy Economics; Risk Management
Hilde Wilkinson-HerbotsApplications of Probability and Stochastic Processes to Problems in Genetics; Epidemic Models

Current and Recent Externally Funded Projects

  • 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.
  • 2019-2020: PI Guillas, Co-I Beskos. Real-Time Advanced Data assimilation for Digital Simulation of Numerical Twins on HPC (RADDISH), EPSRC AI for science and government (ASG) and Alan Turing Institute, £225k. 
  • 2019-2022: PI Guillas, Future Indonesian Tsunamis: Towards End-to-end Risk Quantification (FITTER), Lloyd's Tercentenary Research Foundation, Lighthill Risk Network and Lloyd’s Register Foundation (Alan Turing Institute), £433k.
  • 2019-2021 PI Guillas, EPSRC Tier 2 HPC Resource allocation Panel, Uncertainty Quantification for Tsunamis. Value: 100,000 GPU-hours & 40,000 KNL-hours on Cambridge Service for Data Driven Discovery (CSD3).
  • 2019 PI Guillas, EPSRC IAA Knowledge Exchange and Innovation Funding, "High Resolution Cascadia Tsunami Hazard Model Incorporating Far-Field sources". Value: £36,277 (100% FEC)
  • 2018-2020 PI Guillas, "Uncertainty Quantification Of Multi-scale And Multi-physics Computer Models: Applications To Hazard And Climate Models". Alan Turing Institute, in collaboration with the Universities of Oxford, Warwick and Exeter. Value: £480,509.
  • 2018-2019 PI Guillas, EPSRC IAA Knowledge Exchange and Innovation Funding, Catastrophe modelling for Tsunamis in the Western Indian Ocean. Value: £188,769 (100% FEC)
  • 2018-2019 PI Guillas, EPSRC tier 2 HPC Resource allocation Panel, Uncertainty Quantification for Tsunamis. 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).
  • 2017-2018 PI Guillas, EPSRC M2D (From Models to Decision: Decision Making Under Uncertainty), University of Exeter. Potential large Tsunami Hazards Associated with Landslide Failure along the West Coast of India: from Uncertainties to Planning decisions. Value (without overheads): £23,123.
  • 2017-2018 PI Guillas, NERC/AHRC/ESRCGlobal Challenges Research Fund (GCRF). Co-Is UCL, Brunel, LSE, IISc and IIHS, "Tsunami Risk for the Western Indian Ocean: Steps toward the Integration of Science into Policy and Practice". Value: £198k (100% FEC).
  • 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.
  • Probability, Uncertainty and Risk in the Natural Environment, £683k, NERC NE/J017434/1, Aug 2012 - Aug 2016, PI: Chandler.