People
Our core members are data-driven researchers from across Edinburgh who are involved in the promotion and application of the statistical sciences.
Anyone interested in becoming a member should contact the Director. for more information. Everyone is free to sign up to the mailing list https://mlist.is.ed.ac.uk/lists/subscribe/cfs-news
You can find information about the CfS Organisation and management via the Organisation page
Mike Allerhand
Research interests
Statistical modelling, machine learning, statistical programming, and numerical analysis. Mike is an expert R programmer and has skills in data visualization, data reduction, feature engineering, statistical modelling, and machine learning for inference, prediction, and classification.
Keywords (methods)
generalised and additive regression models, Bayesian inference, networks and graphs, state-space methods, machine learning, pattern recognition
Keywords (applications)
speech and auditory modelling, cognitive ability and personality, biostatistics, neuropsychology
Niall Anderson
Research interests
Medical statistician, working in collaborative research within public health and clinical medicine. Range of experience across statistical genetics and genetic epidemiology, inflammatory bowel disease research, prediction of ventilator-acquired pneumonia, as well as more general clinical research topics. Heavily involved in statistical education and consulting.
Keywords (methods)
modelling, diagnostic tests, mixed models, teaching, consultancy
Keywords (applications)
public health, epidemiology, clinical trials, consulting, education
Jake Ansell (Chair, Steering Committee)
Research interests
Applied statistician/management scientist applying statistical and optimisation methodologies to problems in the domain of business and engineering. Aim is to develop new approaches to issues that relate to enhancing performance of systems and exploring issues across range of areas.
Keywords (methods)
reliability and maintenance, credit scoring, risk management, optimisation
Keywords (applications)
banking, financial capability, engineering (reliability), SMEs, marketing
Michele Belot
Research interests
Evaluation of economic policies in the domains of health, labour and education. Currently my two main research agendas relate to dietary habits and advice to job seekers and in both cases I am interested in studying behavioural change.
Keywords (methods)
difference-in-differences analysis, discrete choice models, experiments, survival analysis
Keywords (applications)
dietary choices, educational achievements, job search behaviour
Natalia Bochkina
Research interests
My research interests include statistical theory, methodology and applications. I am interested in developing statistical methods for challenging applied problems, and making them efficient and robust. I am also interested in developing robust statistical inference based on fast approximate methods, e.g. coming from machine learning
Keywords (methods)
Bayesian inference, nonparametric inference, wavelet methods, inverse problems, model misspecification, graphical models
Keywords (applications)
biology, genomics, medicine, geoscience
Tom Booth
Research interests
I am an applied quantitative methods researcher with a primary interest in individual differences, organisational psychology and health. I am interested in the application of statistical models (broadly speaking generalized latent variable models) to large scale, secondary, longitudinal data.
Keywords (methods)
structural equation modelling, psychometrics & generalized latent variable models, longitudinal data
Keywords (applications)
epidemiology, individual differences, organisational psychology, health
Andrew Cairns
Research interests
Research into the modelling, measurement and management of mortality and longevity risk in life insurance and pensions. Development of the best models for understanding historical mortality improvements, and for predicting future mortality rates. Identification of mortality inequalities across national populations.
Keywords (methods)
Bayesian methods, financial mathematics, simulation, stochastic modelling
Keywords (applications)
cause of death analysis, financial risk management, insurance, model risk, mortality and longevity risk, mortality inequality, pensions, predictive analysis for mortality
Tim Cannings
Research interests
My research interests are broadly in the area of statistical methodology and theory, including statistical learning problems, nonparametric methods, high-dimensional data and semi-supervised learning. My work is primarily motivated by the recent, rapid, developments in technology, which have resulted in new complex data structures. In particular, we now have the ability to collect and store vast amounts of data routinely, this poses new challenges for statisticians and data scientists.
Keywords (methods)
high-dimensional, nonparametric, random projections, data perturbation, noisy and incomplete data
Keywords (applications)
big data analytics, cancer therapy, genomic data
Damien Clancy
Research interests
Stochastic modelling of infectious disease spread, including epidemic models and models for endemic infections; the effects of population heterogeneities on infectious spread; veterinary applications. Bayesian inference, particularly for infectious disease models, and also for ecological models.
Keywords (methods)
Bayesian inference, stochastic models, Markov processes, epidemic models
Keywords (applications)
epidemiology, veterinary epidemiology, ecology
Nick Colegrave
Research interests
My research interests are in the interface between ecology and evolution. I am interested in developing simulation approaches to power analysis and improving experimental design and statistics among biological researchers.
Keywords (methods)
Power analysis by simulation
Keywords (applications)
ecology, evolution, statistics education
Helen Colhoun
Research interests
Using electronic health data to model the risk of diabetes complications. Availing of linkage to biobanks to generate and examine other high dimensional data including molecular and 'omics data for prediction. Focus on understanding the pathogenesis and means of prevention of diabetic complications with studies ranging from genetic epidemiology and biomarker studies through to clinical trials. Large scale epidemiological analyses for informing health policy.
Keywords (methods)
survival analyses, growth curve analyses, prediction performance, genome wide association studies (GWAS)
Keywords (applications)
epidemiology, genetics, diabetes, cardiovascular disease, kidney disease
Jonathan Crook
Research interests
My interests are in exploring statistical and econometric issues in all aspects of credit risk. These issues include sample selection problems, model risk, dynamic models, missing data issues and involve parametric and non-parametric methodologies . The application areas typically involve probability of default, loss given default, exposure at default and stress testing.
Keywords (methods)
APC models, Bayesian inference, classification, intensity models, machine learning, missing data, mixed models, panel models, sample selection models, spatial models, survival analysis
Keywords (applications)
bank capital modelling, credit scoring, stress testing
Andrew Curtis
Research interests
I focus mainly on Bayesian design, image creation, and image interpretation problems. I also study how to obtain robust a priori information from humans to drive Bayesian inference and decision making processes. I tend to create images of the structure or properties of media using acoustic or elastic waves, or electrical resistivity data. I develop optimal elicitation methods and interrogation theory to analyse uncertainties in human-derived information and decisions.
Keywords (methods)
Bayesian inference, optimisation, expert elicitation, design, interrogation, Monte Carlo, hidden Markov models, wave physics
Keywords (applications)
geoscience, geophysics, geology, non-destructive testing, medical imaging, seismic, acoustic, ultrasound, resistivity
Miguel de Carvalho (Co-Director, Communication and Engagement)
Research interests
My research interests are eclectic. I am an applied mathematical statistician with a variety of research interests including, inter alia, statistical inferences for small-probability events, geometrical statistics, methods for data visualization and graphical learning, econometrics, and medical diagnostic assessment.
Keywords (methods)
Bayesian inference, nonparametric inference, empirical likelihood, singular spectrum analysis, statistics of extremes
Keywords (applications)
medicine, business, macroeconomics, finance, risk
Chris Dent
Research interests
Energy systems analysis. Electricity security of supply risk. Renewable resource modelling. Use of modelling and data in government, including model calibration, uncertainty analysis, role of modelling within decision processes, and communication of results beyond the technical modelling community. Industrial applications of mathematics.
Keywords (methods)
statistical emulation, uncertainty quantification, time series, optimization, applied probability
Keywords (applications)
risk, energy, electricity, government, communication, renewables, variable generation, model calibration, industrial applications
Goncalo dos Reis
Research interests
My research is at the interface of applied probability, stochastics, and statistics. Currently I am investigating applications of machine learning to a variety of problems in financial risk and have several projects with financial industry partners on topics of model calibration, risk computation, model development and software development.
Keywords (methods)
Hawkes processes and point processes, hidden Markov models, high-dimensional sampling algorithms, large deviations principles, Markov chain Monte Carlo and simulation, mean-field and related techniques in Wasserstein spaces, Monte Carlo, optimal control, transportation and concentration of measure, uncertainty quantification
Keywords (applications)
banking risk, game theory, machine learning, mathematical finance, probabilistic numerics, risk analysis, risk management
Meriem El Karoui
Research interests
My research focuses on the integration of bacterial physiology in the understanding of the molecular processes underlying DNA maintenance and antibiotic tolerance. I have established a group of researchers with merged expertise from mathematics, microbiology and biophysics.
Keywords (methods)
stochastic modelling
Keywords (applications)
DNA repair, genetics, microbiology
Jonathan Gair (Director)
Research interests
Development of data analysis techniques for and scientific exploitation of observations made by gravitational wave detectors, including LIGO, LISA, pulsar timing and the Einstein Telescope. Statistical emulation of complex process models in physics and environmental science. Assessment of ecosystem services provided by habitat restoration
Keywords (methods)
Bayesian inference, statistical emulation, uncertainty quantification, Gaussian processes, hierarchical models
Keywords (applications)
ecology, astrophysics, gravitational waves, LIGO, LISA, pulsar timing, hydrology, NIRAMS
Gavin Gibson
Research interests
My research deals with methods of parameter estimation and model assessment for spatio-temporal stochastic models with applications mainly in infectious disease epidemiology where particular challenges arise due to the typically incomplete nature of observations. Working mainly in the Bayesian framework, while drawing on classical methods, I make extensive of data augmentation and computational methods. My work has involved extensive collaboration with biological and medical scientists.
Keywords (methods)
Bayesian inference, Markov chain Monte Carlo, model assessment and comparison, posterior predictive methods, spatio-temporal models
Keywords (applications)
arboreal pathogens, built environment, image processing, laser imaging systems, phylodynamics, veterinary pathogens
Michael Gutmann
Research interests
Developing methods for efficient statistical inference and model-based experimental design and using them to solve challenging problems in the natural sciences.
Keywords (methods)
approximate Bayesian computation, likelihood-free inference, Bayesian experimental design, implicit models, unnormalised/energy-based models, unsupervised machine learning
Keywords (applications)
computational biology, epidemiology of infectious diseases
Jarrod Hadfield
Research interests
I am an evolutionary biologist mainly working in the area of quantitative genetics. I develop statistical methods and algorithms for analysing data commonly collected by evolutionary biologists, some of which are general (for example, hierarchical models for non-Gaussian data) and some of which are more specific (for example, pedigree reconstruction from genetic markers).
Keywords (methods)
Bayesian inference, hierarchical models, pedigree reconstruction, phylogenetic comparisons
Keywords (applications)
ecology, quantitative genetics, evolutionary biology
Gabriele Hegerl
Research interests
Detecting, attributing and understanding observed climate variability and change. Focus on variability and change in climatic extremes and precipitation, estimating climate sensitivity, and use of palaeo proxy data to study climate variability and change during the last millennium
Keywords (methods)
attribution methods, Bayesian analysis, orthogonal functions, Monte Carlo methods
Keywords (applications)
statistical climatology, climate change, extreme weather and climate events
Vanda Inacio De Carvalho
Research interests
Development of (Bayesian) flexible methods and software for biostatistical applications, in particular, for the evaluation of medical tests/biomarkers.
Keywords (methods)
Bayesian inference, computational statistics, nonparametric methods
Keywords (applications)
biostatistics, medicine
Ruth King
Research interests
I am an applied statistician, developing new statistical methodology motivated by real problems, primarily within the areas of ecology and healthcare. Particular interests include constructing novel statistical models, involving for example individual heterogeneity, memory and integrated data analyses; and associated efficient model-fitting algorithms
Keywords (methods)
Bayesian inference, capture-recapture, hidden (semi-)Markov models, integrated models, missing data, state-space models
Keywords (applications)
epidemiology, medicine, ecology
Stuart King
Research interests
I work in applied mathematics with an interest in data science techniques and problems. In particular I am interested in developing statistical and machine learning techniques to images and image sequences applied to data in a range of areas, including satellite and aircraft based Earth observation through to medical imaging.
Keywords (methods)
clustering, classification, change detection, image processing
Keywords (applications)
ecology, remote sensing, satellite images, medical applications
Alison Koslowski (Co-Director, CHASS)
Research interests
I generally work with large scale cross-national social survey data in the pursuit of a better understanding of questions concerning the labour market, care work, and gender equality.
Keywords (methods)
social science survey data (data collection and analysis), longitudinal data analysis
Keywords (applications)
social policy, sociology, demography
Steff Lewis
Research interests
I am one of the leads of the statistics team in Edinburgh Clinical Trials Unit, and my research interests are around many practical areas of design, conduct and analysis of randomised trials. I've been particularly involved in guidance for Statistical Analysis Plans and anonymisation of trial datasets, and choice of minimisation variables (and the use of random elements in minimisation). I also dabble in meta-analysis and prognostic models.
Keywords (methods)
anonymisation, baseline adjustment, meta-analysis, randomisation
Keywords (applications)
clinical trials, medicine
Finn Lindgren (Co-Director, Events)
Research interests
Developing probabilistic models for spatial and space-time phenomena, suitable for ecological, climatological, and general environmetrics applications, as well as medical imaging problems. Computational solutions for Bayesian statistics with hierarchical generative models.
Keywords (methods)
Bayesian inference, Gaussian processes, random fields, Gaussian Markov random fields, stochastic partial differential equations, fast approximate inference
Keywords (applications)
ecology, medical imaging, animal abundance, biodiversity, climatology, historical temperature reconstruction, fMRI
Samantha Lycett
Research interests
Evolution and epidemiology of viruses and bacteria, including machine learning techniques and Bayesian phylogenetics to investigate cross species transmissions, host adaptations, epistatic interactions, phylodynamics and phylogeography. I'm developing fast computational methods and simulation tools to infer transmission patterns of animal and livestock pathogens (including in missing data situations), and methods to extract predictive factors for disease risk and new strain generation
Keywords (methods)
Bayesian inference, phylodynamics, phylogeography, machine learning methods, network inference, approximate methods, stochastic simulations
Keywords (applications)
epidemiology, sequence data, viruses, bacteria, animal and zoonotic pathogens, disease networks, pathogen evolution
Ian Main
Research interests
Processes that lead up to catastrophic failure events, from earthquakes, rock fracture, and volcanic eruptions to failure of building materials and bridges. Population dynamics of localised brittle failure as a complex, non-linear (unreasonable) system, and in quantifying the resulting hazard
Keywords (methods)
Bayesian analysis, Monte Carlo methods, multivariate statistics, epidemic-type stochastic models for point processes
Keywords (applications)
probabilistic seismic hazard estimation, prospective earthquake forecasting, communicating risk and uncertainty, hazard mitigation and disaster risk reduction.
Paul McKeigue (Co-Director, CMVM)
Research interests
Methods for molecular and genetic epidemiology, with applications in clinical prediction and personalized medicine. These include using biomarkers or automated scoring of images to predict diabetic complications, to predict drug response in rheumatoid arthritis, and to detect cancer in national screening programmes.
Keywords (methods)
Bayesian hypothesis testing, Bayesian computation, Markov chain Monte Carlo, variational inference, hierarchical shrinkage priors, projection predictive variable selection, deep learning
Keywords (applications)
biomarker discovery, biomarker selection, genetic prediction, precision medicine, risk stratification, image classification
Susan McVie
Research interests
My main area of research currently is around crime and justice inequalities which includes using large survey and administrative datasets to explore issues around the impact of poverty, deprivation and unequal access to services on criminal behaviour and patterns of victimisation. I am also involved in developing new areas of data linkage between law enforcement and public health organisations. I manage a large longitudinal study of offending behaviour and I am involved in developing new areas of research around violent criminal careers
Keywords (methods)
structural equation modelling, longitudinal methods and panel analysis, multi-level analysis, quasi-experimental methods
Keywords (applications)
international crime trends and patterns, youth crime and juvenile justice, criminal careers through the life-course, patterns of violence and homicide, youth gangs and knife crime, policing and crime reduction, stop and search, police use of biometric data
Iain Murray
Research interests
I develop computational methods to perform probabilistic reasoning about unknown parameters, or actions in unknown or changing environments. As these models can be large scale, or require very large numbers of parameters, much of my work lies at the intersection of statistics and machine learning.
Keywords (methods)
Bayesian inference, deep learning, density estimation, Gaussian processes, hierarchical models, Monte Carlo
Keywords (applications)
anything with interesting data and decisions, astrophysics, cosmology
Ken Newman
Research interests
I am interested in applications to and methodology for ecological and environmental statistics. This includes modelling animal population dynamics, estimation of animal abundance, survival, and fecundity. I'm also interested in sampling methods, including spatial sampling, error correction of land use maps, and approximating complex deterministic models with Gaussian processes.
Keywords (methods)
state-space models, sampling, Bayesian hierarchical models
Keywords (applications)
ecology, fish and wildlife management, environment
Matthew Nolan
Research interests
Brain circuit mechanisms that implement computations important for cognition. Focus on spatial cognition, high resolution optical imaging of neural circuitry, electrophysiological recording and analysis of single neurons and networks of neurons, modelling and simulation of neural activity.
Keywords (methods)
neural circuit analysis, electrophysiology, neural modelling
Keywords (applications)
neural circuit computation, spatial cognition
Yiannis Papastathopoulos
Research interests
I am a statistician working at the interface between applied probability and statistical inference. My research focusses on developing statistical models for extreme events through asymptotic characterizations of stochastic processes and random phenomena. This is combined with implementation of Bayesian methods and computationally efficient procedures for statistical inference.
Keywords (methods)
approximate Bayesian inference, spatial statistics and point processes, Markov random fields, Extreme value theory, methods and applications
Keywords (applications)
environment, ocean engineering, pharmaceutical statistics, grid cells, political conflicts
Marcelo Pereyra
Research interests
My research is mainly about new mathematical theory, methods and algorithms to solve challenging inverse problems related to mathematical and computational imaging. I am particularly interested in new Bayesian analysis and computation approaches, and in the synergy between modern stochastic simulation, convex optimisation, and machine learning methodology.
Keywords (methods)
Bayesian inference, convex optimisation., high-dimensional statistics, Markov chain Monte Carlo, uncertainty quantification
Keywords (applications)
Computational imaging, remote sensing, medical imaging
Gareth W. Peters
Research interests
Statistics and machine learning for risk, insurance and finance. Mathematical statistics, computational statistics and stochastic processes.
Keywords (methods)
time series modelling, econometrics, insurance reserve models and capital modelling, spatial temporal modelling and supervised and unsupervised machine learning methodology
Keywords (applications)
risk management, insurance modelling, cyber risk modelling, mortality modelling and demographics, futures modelling, interest rate models, stress testing, portfolio selection and performance assessment, green finance, green bonds, blockchain technology and virtual currencies, regulations research, algorithmic trading and high frequency finance, insurance for extreme weather and climate events.
Chris Ponting
Research interests
Pinpointing DNA changes that predispose individuals to common genetic disease, and determining how such changes alter gene expression and affect development, cells and organs. We apply and combine methods developed by others to address some of the most important questions in genetics and human disease.
Keywords (methods)
deep learning, Mendelian randomisation, genome-wide association studies
Keywords (applications)
complex disease, cancer, DNA/RNA sequence analysis at all scales from single cells to human subpopulations.
Chris Pooley
Research interests
I work on developing fast Bayesian tools and techniques applicable to a broad range of problems. I am developing novel algorithms to help speed up inference and perform fast, reliable model selection. On the applied side I'm looking into incorporating genetics into epidemiology and the analysis of ecological data. I am interested in creating easy to use software to facilitate the widespread use of advanced Bayesian techniques, and I also have a keen interest in deep learning methods, such as convolutional neural networks.
Keywords (methods)
Bayesian inference, capture-recapture, compartmental models, epidemic models, Markov processes, MCMC, mixed models, model selection, stochastic models
Keywords (applications)
ecology, epidemiology, genetics
Gail Robertson
Research interests
I am an applied statistician at the Statistical Consultancy Unit with a background in quantitative ecology and infectious disease epidemiology. I am involved with the development of data analysis methods in a variety of fields including environmental sciences, forensic statistics, and decision modelling
Keywords (methods)
mixed models, spatial analysis, mapping spatial data, temporal data analysis
Keywords (applications)
epidemiology, ecology, environmental science, forensic statistics, decision modelling
Gordon Ross
Research interests
My research centres around the application of statistical and machine learning methods for predicting time series and point processes. Specific interests include: 1) Detection of abrupt changes/anomalies in time series, 2) Bayesian statistics, particularly nonparametric methods, 3) Risk analysis, including financial markets and earthquake forecasting, 4) Retail analytics, 5) Cyber security.
Keywords (methods)
Bayesian inference, time series, nonparametrics, point process
Keywords (applications)
finance, risk, cybersecurity, earthquakes, seismology
Sotirios Sabanis
Research interests
Analysis of Langevin Monte Carlo sampling algorithms (including the unbiased estimators' version, e.g. SGLD) in a non-Markovian environment, i.e. observation data need not to be Markovian, and their applications in Bayesian learning. Any application of these methodologies to financial data is of keen interest to me.
Keywords (methods)
Bayesian inference, high-dimensional sampling algorithms, mathematical finance, stochastic algorithms/approximations
Keywords (applications)
engineering, portfolio management, risk
Guido Sanguinetti
Research interests
Development of data modelling techniques for biological data, with a particular focus on understanding the dynamics and regulation of gene expression. Stochastic models of chemical reaction networks, reaction-diffusion processes
Keywords (methods)
Bayesian inference, graphical models, chemical master equation
Keywords (applications)
next-generation sequencing, epigenomics, gene expression
Linus Schumacher
Research interests
I develop mathematical models of cellular processes in biology, especially the collective behaviour of cell populations. I use a variety of tools, including differential equations, agent-based simulations, and stochastic processes, and the main application areas are tissue development, stem cells, and regenerative medicine. As part of these efforts I am interested in data-driven modelling and practical methods for parameter inference and model comparison.
Keywords (methods)
approximate Bayesian inference, agent-based models, hybrid models, master equations, dynamical systems
Keywords (applications)
developmental biology, stem cells, regenerative medicine, cell migration
Serveh Sharifi Far
Research interests
Analysis of categorical data, fitting models to sparse contingency tables, modelling with Pearson system distributions.
Keywords (methods)
extended maximum likelihood estimate, model's identifiability, parameter redundancy, path analysis
Keywords (applications)
social sciences, genetic data
Valeria Skafida
Research interests
Exploring and understanding changes in children’s health and wellbeing using longitudinal data with a focus on social inequalities and with reference to relevant social policy. Areas of specific interest include infant diet and child nutrition; domestic violence and children's wellbeing.
Keywords (methods)
dimension reduction (principle component analysis), fixed and random effects models, GLM, longitudinal analysis, survival analysis
Keywords (applications)
epidemiology, public health, social policy, sociology
George Streftaris
Research interests
Bayesian statistical modelling and inference, focussed on the development and application of novel methodology used in stochastic processes for partially observed populations. I am particularly interested in inter-disciplinary work involving statistical methodology applied in infectious epidemiology, actuarial mathematics and life sciences.
Keywords (methods)
Bayesian inference, epidemic models, Markov chain Monte Carlo, model assessment, predictive modelling
Keywords (applications)
infectious epidemiology, actuarial mathematics, morbidity, life sciences
Lukasz Szpruch
Research interests
I have a broad research interest in probability theory, mean-field models, stochastic control, statistics and quantitative finance. I am also researching on deep neural networks and reinforcement learning. I have worked with the financial services industry on topics such as model calibration or risk computation.
Keywords (methods)
machine learning, Markov Chain Monte Carlo methods, mean field models
Keywords (applications)
cyber security, energy markets, financial services, insurance
Albert Tenesa
Research interests
The overarching aim of my lab is to understand what drives phenotypic variation in populations. To achieve this aim, we develop computational and statistical tools to analyse genetic and genomic data at scale. We also combine lifestyle and environmental risk factors with genetic risk factors for the prediction of disease risk or complex traits. @GroupTenesa
Keywords (methods)
machine learning, mixed linear models, generalized mixed models, high performance computing, regularization methods
Keywords (applications)
genomics, quantitative genetics, genetic epidemiology, animal breeding, population genetics, statistical genetics
Catalina Vallejos
Research interests
Development, implementation and application of novel Bayesian methodology that is motivated by complex biomedical problems and data types (e.g. those generated by cutting-edge genomic technologies). Development of statistical models that are robust to measurement noise and other sources of unwanted heterogeneity. Implementation of open-source analysis tools
Keywords (methods)
Bayesian inference, hierarchical models, survival analysis, competing risks
Keywords (applications)
biomedicine, single cell transcriptomics, electronic health records
Sara Wade
Research interests
My research interests span Bayesian inference and machine learning. I am particularly interested in nonparametric methods for regression, clustering, and dimension reduction, and computational algorithms for full posterior inference, as well as fast algorithms for approximate inference, based on variational methods and maximum aposteriori estimates.
Keywords (methods)
Bayesian inference, machine learning, clustering, nonparametrics, density regression, Dirichlet process, Gaussian process
Keywords (applications)
medicine, Alzheimer's disease, imaging data, time-to-event data
Chris Williams
Research interests
I am interested in a wide range of theoretical and practical issues in machine learning, statistical pattern recognition, probabilistic graphical models and computer vision. This includes theoretical foundations, the development of new models and algorithms, and applications.
Keywords (methods)
Gaussian processes, time series understanding, condition monitoring, scene understanding, messy data, unsupervised learning
Keywords (applications)
image and scene analysis, intensive care unit monitoring, data science for science
Amy Wilson
Research interests
I am an applied statistician interested in statistical modelling for applications in energy and the law. I have worked on a variety of applied problems. These have included assessing the risk of long-term electricity outages, quantifying uncertainty in energy policy models, evaluating the strength of forensic evidence (for e.g. drug traces on banknotes) and quantifying uncertainty in the outcome of civil legal cases.
Keywords (methods)
Bayesian inference, statistics of extremes, uncertainty quantification, time series modelling, statistical inference
Keywords (applications)
engineering, energy policy, forensic science, law, electricity shortfalls
Andrea Wilson
Research interests
Development of statistical and mathematical models and computational tools to determine how the genetics of individuals and diverse non-genetic factors together influence the dynamics of infectious diseases and their impact on the health and performance of individuals and of entire livestock populations.
Keywords (methods)
Bayesian inference, hierarchical mixed models, statistical genetics, random regression models, ordinary differential equations, stochastic modelling of non-linear dynamic processes, social network analysis
Keywords (applications)
infection dynamics, disease transmission, quantitative genetics applied to livestock populations, individual and group aggression, resilience
Maria Wolters
Research interests
In my work, I leverage data and technology to support people with chronic conditions in living rich and meaningful lives. I have expertise in evaluating services, apps, and products, and I am particularly interested in helping people take control of and make sense of their own data.
Keywords (methods)
missing data, human-data interaction, mixed qualitative and quantitative methods, questionnaire design and analysis, evaluation
Keywords (applications)
medicine, design, sports, wellbeing
Bruce Worton
Research interests
My interests are primarily in research involving statistical modelling of challenging problems and related statistical inference techniques. I have undertaken collaborative research with Scotland's Rural College (SRUC) and the James Hutton Institute, Dundee, concerned with modelling the movements of larvae using flexible diffusion processes to characterize the behaviour of larvae when exposed to attractant/repellent compounds
Keywords (methods)
statistical modelling, applied statistics, bootstrap computation, likelihood inference, efficient Bayesian inference
Keywords (applications)
biology, ecology, entomology, geosciences