Data science
Our expertise spans the full data science life-cycle: from information management and privacy, via machine learning and representational logics, to practical applications in bio-health informatics.
Our facilities
We boast an incredible array of facilities, making our innovative data science research possible.
A key feature of our approach is closely coupling methodology and application. This creates a self-fulfilling loop, where challenging real-world problems drive the methodology research agenda, but also provide a natural route to exploiting new algorithms and methods.
We believe this deeply multidisciplinary approach is one of the distinctive features of data science at Manchester.
Areas of expertise
Our researchers focus their work in the following specialist areas:
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Imaging science
We use and develop advanced techniques to extract useful information from images and videos from a range of domains, including medicine, engineering, and biology.
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Information management
We design, develop and build state of the art data and knowledge management systems -- spanning from formal underpinnings in knowledge representation and logic, to challenging interdisciplinary work.
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Machine learning and robotics
We develop and apply novel statistical Machine Learning methodologies, from theory to application, and push forward the state of the art in Human-Robot interactions with our Cognitive Robotics Lab.
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Natural language processing and text mining
We develop NLP and text mining techniques to provide insights for social scientists, biologists, and neuroscientists. Our strong interdisciplinary foundations support a world leading expertise in information extraction.
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Postgraduate research projects
Data science projects
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Automatic Music Generation via Deep Learning
- Biologically-Plausible Continual Learning
- Blockchain-based Local Energy Markets
- Building Machine Learning Models Using Matrix Factorisation
- Contextualised Multimedia Information Retrieval via Representation Learning
- Data Integration & Exploration on Data Lakes
- Data Wrangling
- Deep Learning for Temporal Information Processing
- Design and Implementation of an FPGA-Accelerated Data Analytics Database
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Fishing in the Data Lake
- In between structure and texture: Strexture
- Information Component Analysis via Deep Learning
- Machine Learning and Cognitive Modelling Applied to Video Games
- Managing the data deluge for Big Data, Internet-of-Things, Industry 4.0 environments
- Minimum Description Length: An information-theoretic approach to the groupwise study of image information
- Multi-task Learning and Applications
- Problems in large graphs (e.g., social networks, VANETs)
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Social Human-Robot interaction using visual object recognition and hand pose estimation
- Specifying and Optimising Data Wrangling Tasks
- Text Analytics and Blog/Forum Analysis
- Type 1 Diabetes: Accurate Prediction of Glucose Absorption from Food
- Unlocking Open Data through Wrapper Generation
- Web Users with Cognitive Disabilities: Interaction Differences and Coping Strategies
- Zero-Shot Learning and Applications
Richard Banach projects
Ke Chen projects
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Automatic Music Generation via Deep Learning
- Biologically-Plausible Continual Learning
- Contextualised Multimedia Information Retrieval via Representation Learning
- Deep Learning for Temporal Information Processing
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Information Component Analysis via Deep Learning
- Machine Learning and Cognitive Modelling Applied to Video Games
- Multi-task Learning and Applications
- Zero-Shot Learning and Applications
Angelo Cangelosi projects
- Early Stage Researcher (PhD student) in Mobile Application and AI for Language Learning (H2020 eLADDA; Collaboration between Sponge and the University of Manchester)
- Human-Robot Collaboration for Flexible Manufacturing (iCAse PhD with BAE Systems)
- Social Human-Robot interaction using visual object recognition and hand pose estimation
Andre Freitas projects
Aphrodite Galata projects
Simon Harper projects
Dirk Koch projects
Tingting Mu projects
Mustafa Mustafa projects
Goran Nenadic projects
Norman Paton projects
Rizos Sakellariou projects
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed machines
- Managing the data deluge for Big Data, Internet-of-Things, Industry 4.0 environments
- Problems in large graphs (e.g., social networks, VANETs)
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing