The Department works closely with local, regional and global industries and third sector organisations in order to support and strengthen our research agenda.
The excellent facilities and the ideal location in one of the most intense concentrations of Information Technology industry in the UK provide a thriving research environment for our computer scientists.
Environmental science depends on the analysis of large volumes of observational data and on sophisticated simulation schemes, coupling different physics on multiple time and special scales, demanding both supercomputing and specialised data analysis systems. ACES research themes address the future of the relevant computing and data systems. Current projects include work on developing software to aid scientific programming on next generation computing systems, on cloud computing, on exploiting machine learning in environmental science, and on new software and hardware systems for handling the high volume and high velocity data typical of environmental science workflows.
Research in image processing and computer vision is concerned with the computational issues of perception and reasoning in relation to image interpretation. Current research activities focus on automated CCTV analysis for safety, security and threat assessment, biometrics and environmental monitoring. In particular, specific research activities include model-based methods for people and vehicle surveillance, appearance-based modelling, pose and structure recovery, path-based tracking of known objects in 3D using single or multiple cameras, remotely sensed data interpretation for environmental monitoring and precision agriculture, as well as biometrics in automated border control.
Data Science and Artificial Intelligence (DSAI)
Research on Machine Learning, Data Mining and Big Data Analytics is devoted to algorithms, techniques and applications for data-driven knowledge discovery from large amounts of data. Algorithms cover a range of predictive and descriptive methods, such as clustering, classification, subgraph mining, Stream Mining, Bayesian inference, artificial neural networks, association rules, generative adversarial networks multi-task learning/competitive learning verification, synthesis of artificial neural networks probabilistic modelling, and semantic workflow integration and decision support. Application domains include life sciences, neuroscience, climate science, and industrial and business sectors.
The research laboratories aggregate specific activities of the academic supervisors. In addition the Department also has a large and dedicated PC lab for PhD students of all research groups.
- Computer Vision Group lab
- Advanced Computing for Environmental Science lab
- Artificial Intelligence lab
- Big Data Analytics lab
- Cyber-Physical & Embedded Data Intelligence lab
- CS PhD lab
The Department applies its research expertise in collaborations and application areas across the University and externally to maximise the societal and commercial impact of its work. There has been a sustained pattern of large-scale collaborative projects led by the research leaders in the Department including in areas of applications of AI, Data Science, Computer Vision, Big Data Analytics, High-Performance Computing, Cyber-Physical Systems and Service-Oriented Architectures.
We are building on existing strong industrial engagements, in both teaching and research, and forging new relationships, particularly within the Thames Valley region.
There is also a particular focus on developing interdisciplinary activity and collaborative projects with the wider School and wider research community, including two NERC national centres, the National Centre for Atmospheric Science (NCAS) and the National Centre for Earth Observation (NCEO). The department also benefits from close working relationships with the Institute for Environmental Analytics, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Met Office.