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Data Science

Data really powers everything that we do.

Research activities in the data science area are concerned with the development of machine learning and statistical methods, their theoretical foundations, and applications. 

The group's expertise includes the development of scalable machine learning methods, computational aspects of statistical methods, large-scale statistical inference, nonparametric estimation, representation learning, functional data analysis, optimisation for machine learning, and advanced computational methods such as Markov Chain and sequential Monte Carlo for Bayesian inference. 

The areas of applications include the design of novel methods for understanding user behaviour, analysis of social data, modelling and inference for information cascades and epidemic processes that arise in social networks and biomedical applications, as well as algorithms for development of next-generation artificial intelligence systems. 

The group members are actively involved in teaching on the MSc Data Science degree programme which provides training in data science methods. The programme provides a thorough grounding in theory, much of it at a high mathematical level, as well as gaining practical skills of applied data science, enabling one to apply advanced data science methods to investigate real-world questions.  

Academic Staff

M Barreto 2021

Marcos Barreto - Assistant Professorial Lecturer

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Yining Chen - Associate Professor

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Moez Draif

Moez Draief - Visiting Professor in Practice

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Dr Kostas Kalogeropoulos 200x200

Kostas Kalogeropoulos - Associate Professor

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Joshua Loftus

Joshua Loftus - Assistant Professor 

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Dr Xinghao Qiao200x200

Xinghao Qiao - Associate Professor

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Francesa Panero

Francesca Panero - Assistant Professor 

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Chengchun Shi

Chengchun Shi - Assistant Professor

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Zoltán Szabó

Zoltan Szabo - Professor

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Milan Vojnovic

Milan Vojnovic - Professor

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Tengyao Wang

Tengyao Wang - Associate Professor

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Research Students