Machine Learning
Machine Learning is the study of computer algorithms that improve automatically through experience (Tom Mitchell, 1997).
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.
| Name | Expertise |
|---|---|
| Federico Botta | Machine Learning, Network Analysis, Time Series Analysis, Statistical Modelling, Social Media, Data Science for Public Policy, Spatial Data Science |
| Chico Camargo |
Machine learning, Natural language processing, Time series analysis, Network analysis, Software engineering, Signal processing |
| Optimisation, Machine learning, Bayesian inference, Statistical modelling, Frequentist inference | |
| Bioinformatics, Optimisation, Machine learning | |
| Saptarshi Das | 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 |
| Optimisation, Machine learning, Machine vision, Emulation / uncertainty quantification, Signal processing | |
| Jonathan Fieldsend | Optimisation, Software engineering, Machine learning, Emulation / uncertainty quantification |
| Zeyu Fu | Machine vision, machine learning, medical image analysis, visual surveillance (health and environment) |
| Oliver Hauser | Causality, Game theory, Machine learning, Clinical trials, Time series analysis |
| Raphaëlle Haywood | Physical Modelling, Machine Learning, Bayesian Inference, Time Series Analysis; |
| Jia Hu | Machine learning, Communications, High performance computing |
| Edward Keedwell | Optimisation, Machine learning |
| Mark Kelson | Causality, Statistical modelling, Machine Learning, Clinical trials, Frequentist inference |
| Ke Li | Optimisation, Software Engineering, Machine Learning. I'm working on multi-objective optimization and decision-making, machine learning and applications in various areas including but not limited to software engineering and synthetic biology |
| David Llewellyn | Causality, Machine Learning, Statistical Modelling, Clinical Trials, Precision Medicine, Population-based and clinical datasets |
| Chunbo Luo | Machine learning, Machine vision, Communications, Signal processing |
| Cyril Morcrette | Physical Modelling, Machine Learning, Emulation/Uncertainty Quantification, Frequentist Inference, High Performance Computing, Signal Processing, Atmospheric Sciences, Environmental Sciences, Meteorology, Atmospheric Physics |
| Markus Mueller | Optimisation, Physical modelling, Machine learning, Time series analysis, Signal processing |
| Bernard Nortier | Optimisation, Machine learning, Bayesian inference, Time series analysis, Statistical modelling, Emulation / uncertainty quantification, Frequentist inference |
| Mario Recker | Computational biology, Machine learning |
| David Richards | Optimisation, Causality, Physical Modelling, Software Engineering, Machine Learning, Bayesian Inference, Time Series Analysis, Frequentist Inference, High Performance Computing, Statistical Modelling |
| Sareh Rowlands | Machine Learning, Machine Vision |
| Stefan Siegert | Spatial statistics, Physical modelling, Software engineering, Machine learning, Bayesian inference, Time series analysis, Statistical modelling, Emulation / uncertainty quantification, Frequentist inference |
| Joel Tabak | Machine Learning, Machine Vision, Physical Modelling, Computational Neuroscience |
| Danny Williamson | Decision theory, Optimisation, Machine learning, Bayesian inference, Statistical modelling, Emulation / uncertainty quantification |
