Data Science and Statistical Learning theme

In the decades since Professor George Alfred Barnard's retirement in 1975 our department has continued to expand it's expertise and knowledge in this important field of research, the importance of which has significantly increased in the 21st century. Professor Graham Upton joined the department in 1973 and retired in 2014. He authored several text books in statistics and data science.

Nowadays, our department leads on various data science initiatives, for example it is an institutional member of the European Association for Data Science (EuADS) founded in 2015, and it organised at Essex the European Conference on Data Analysis (ECDA2015).

As a result, members of this theme work on a broad range of data science methodologies covering:

• artificial intelligence,
• statistical learning,
• computational statistics,
• epidemiology,
• bioinformatics,
• time series,
• environmental statistics.

The theme has collaborations and partnerships with the health sector, biomedicine, digital industry and government, providing a steady stream of research applications and opportunities which develop strong research impacts.

Since 2014, Professor Lausen has led successful and ongoing Knowledge Transfer Partnerships (KTPs) with Profusion and Mondaq, using optimal tree ensembles (OTE) and other statistical learning methods established by the theme to help develop their business models. Our work with Profusion was awarded Best KTP Partnership of the Year in 2018, while Mondaq was recognised as Winner of Best KTP Partnership: SME in 2019. Additionally, Professor Lausen, Dr Harrison, Dr Hadjiantoni and Dr Mahmoud work together with the Profusion Data Academy and Mondaq to deliver industry-based research lead data science education and placement opportunities within our courses in data science.

Dr Hadjiantoni and Dr Gutierrez-Roig have opened up a new direction of impact-driven research with their KTP linked to the estate agent Strike. This project will develop an AI-driven recommender system that fuses heterogenous data streams and utilises knowledge graphs as well as other machine-learning methods.

Dr Bailey is a co-founder of the interdisciplinary ANIMATE (ANImal Movement AT Essex) research group, which links researchers across the University, with partner organisations such as CEFAS. The department has a long history of research applying mathematical and data science approaches to the wider life sciences.