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Institute for Data Science and Artificial Intelligence

Statistical Modelling

A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (Wikipedia).

If you're looking for a data scientist to work with on a research project or someone to discuss potential methodologies with for a research problem, then you search for the topic you need or alternatively use the A-Z button to search the full list of data scientists.

Tinkle Chugh

Optimisation, Machine learning, Bayesian inference, Statistical modelling, Frequentist inference

Name  Expertise 
Pallavi Banerjee Statistical modelling, Administrative datasets
Federico Botta Machine Learning, Network Analysis, Time Series Analysis, Statistical Modelling, Social Media, Data Science for Public Policy, Spatial Data Science
Peter Challenor  Statistical modelling, Emulation / uncertainty quantification
Saptarshi Das Computational intelligence, Optimisation, Physical modelling, Machine learning, Bayesian inference, Time series analysis, Statistical modelling, Emulation / uncertainty quantification, Frequentist inference, High performance computing, Signal processing, Control Systems, Image Processing
Riccardo Di Clemente Human Mobility, Computational Social Science, Network Theory, Physical modelling, Network analysis, Statistical modelling
Samuel Engle Causality, Bayesian Inference, Statistical Modelling, Frequentist Inference, Decision Theory
Livio Fenga Time Series Analysis, Statistical Modelling, Signal Processing, Misinformation
Eilis Hannon Software Engineering, Statistical Modelling, Frequentist Inference, Bioinformatics
Cavaliere Giuseppe Time Series Analysis, Statistical Modelling, Frequentist Inference
Christis Katsouris Causality, Network Analysis, Statistical Modelling, Time Series Analysis
Mark Kelson Causality, Statistical modelling, Machine Learning, Clinical trials, Frequentist inference
Sebastian Kripfganz Causality, Software Engineering, Time Series Analysis, Statistical Modelling, Frequentist Inference
David Llewellyn Causality, Machine Learning, Statistical Modelling, Clinical Trials, Precision Medicine, Population-based Clinical Datasets
Tj McKinley Bayesian inference, Statistical modelling
Anna Mountford-Zimdars Statistical modelling
Nitzan Peri-Rotem Causality, Statistical modelling, Frequentist inference, Survival analysis
Chris Playford Statistical modelling, Frequentist inference
   
David Richards Optimisation, Causality, Physical Modelling, Software Engineering, Machine Learning, Bayesian Inference, Time Series Analysis, Frequentist Inference, High Performance Computing, Statistical Modelling
Stefan Siegert Spatial statistics, Physical modelling, Software engineering, Machine learning, Bayesian inference, Time series analysis, Statistical modelling, Emulation / uncertainty quantification, Frequentist inference
David Stephenson Environmental statistics, Forecast verification, Physical modelling, Time series analysis, Statistical modelling, Frequentist inference
Krasimira Tsaneva Physical Modelling, Network Analysis, Statistical Modelling, Emulation/Uncertainty Quantification, Time Series Analysis. Experience with applications to Biology, Medicine and Healthcare
Danny Williamson Decision theory, Optimisation, Machine learning, Bayesian inference, Statistical modelling, Emulation / uncertainty quantification