Digital maritime

Driving digital maritime innovation.

Advancing the digital transformation of maritime operations through artificial intelligence (AI), geospatial data science, digital twins, simulation environments, and autonomous systems. Our research empowers safer, more efficient, and decarbonised maritime networks.

Our expertise

AI and machine learning for operations

We use artificial intelligence (AI) and machine learning to help make ports and coastal environments work more efficiently, safely, and sustainably. Our researchers bring together advanced data analysis, computer modelling, and new sensing technologies—such as satellite and land‑based radar—to solve real‑world challenges. This includes improving day‑to‑day port operations to reduce carbon emissions, as well as developing innovative ways to monitor how coastlines and underwater landscapes change over time.

Digital twins and data-enabled decarbonisation at seaports

The University is leading research into digitalisation for operational efficiency and greenhouse gas (GHG) emission reduction at container ports, applying machine learning and optimisation to improve port yard operations and cut emissions. Led by Professor Dongping Song from the Centre for Supply Chain Research, and in collaboration with organisations such as the Port of Felixstowe, the aim is to build predictive models that enhance container handling efficiency and reduce carbon emissions at major container terminals.

Smart logistics and decision support systems for next-generation ports

The University is developing smart logistics and decision support systems for next-generation ports, creating software to optimise crane and yard operations, manage energy efficiently, and capture and process port data. Led by Professor Andy Lyons, this project delivers digital tools that enhance operational decision-making, support sustainable energy management, and improve efficiency across port and shipping operations.

Centre for Doctoral Training (CDT) in Distributed Algorithms

The University leads this EPSRC-funded CDT in Distributed Algorithms in collaboration with STFC Hartree, IBM Research, The Alan Turing Institute, and more than 20 partners, training 60 PhD students to become highly skilled data scientists. Their research supports defence, security, and advanced manufacturing, using high-performance computing and data-driven optimisation to enhance safety and industrial efficiency.

Example research projects include: