Our Research

Our work can have direct impact and help businesses thrive through Knowledge Transfer Partnerships. Through KTPs our researchers can evidence the value and impact of their work, while businesses benefit from expertise and cutting-edge research techniques.

Some of our KTPs have included:

• Working with the Port of Felixstowe to improve efficiency of complex scheduling processes. We assisted in the development of optimisation algorithms using artificial intelligence, which helped with both scheduling staff resources and solving scheduling problems. This reduced waste and improved customer service.
• Carrying out a data science KTP with knowledge resource company Mondaq that helped them make the most of large data sets. They were awarded Winner of Best KTP Partnership 2018.
• Members of our data science group are currently working on a KTP project with online grocery company Ocado, that will utilise Big Data with machine learning and forecasting to improve delivery efficiency, which will reduce cost to the company and the carbon footprint of deliveries.

Our research is interdisciplinary and has impact across areas as diverse as social care, mathematics education, and animal welfare, with examples including:

• Catalyst Project - Improving community services for vulnerable people - A group of researchers from our school contributed to the "Identifying 'at risk' adults and children" initiative in this project.
• Machine learning for recognising tangled 3D objects - Funded by the Leverhulme Trust, this project will use machine learning to look at how we can teach computers to understand the 3D world, without using deep neural networks.
• Cow tracking - We're combining animal behaviour data, gathered using wireless tracking sensors, with mathematics, to help predict early signs of illness or other medical episodes in cows. By giving farmers an early indication of problems, we can improve cow health and welfare.
• Algorithmic fair division in dynamic, socially constrained environments - In this project we are developing a computer algorithm that will ensure fair division of indivisable assets between parties that have a claim on the asset (such as a valuable painting in a divorce case).
• Demand forecasting and dynamic pricing for e-grocery fulfilment - This Knowledge Transfer Partnership project, run with online delivery company Ocado, will improve delivery efficiency using Big Data, machine learning and forecasting.

Academics in our school have published in a range of journals related to their specialist areas within mathematics and data science including:

• European Journal of Operational Research
• Ecology
• Biostatistics
• Statistics in Medicine
• Statistics and Computing
• Bernoulli
• Journal of Applied Probability
• Physica A: Statistical Mechanics and its Applications
• Frontiers in Computational Neuroscience
• Chaos, Solitons and Fractals
• Physical review E.
• Advances in Mathematics
• Journal of Algebra
• Transactions of the American Mathematical Society
• Journal of Physics A: Mathematical and Theoretical
• Journal of Mathematical Physics
• International Mathematics Research Notices
• Memoirs of the American Mathematical Society
• Math Zeitschrift
• Journal of Pure and Applied Algebra

The recent pandemic saw academics from across the University come together to work on a range of projects aimed to understand COVID-19, including how it spreads, and how we can reduce the impact on services and society.

We have contributed our expertise in mathematics and data science into a range of research around COVID-19:

• Dr Stella Hadjiantoni and Dr Andrew Harrison worked with colleagues from across the University on a project that helped an NHS Trust manage its resources.
• Dr Chris Antonopoulos has published two papers on COVID-19 in Chaos, Solitons & Fractals; "A SIR model assumption for the spread of COVID-19 in different communities", and "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic".