Human centred computing
As technology becomes increasingly ubiquitous, our relationship with it is changing.
Our facilities
We boast an incredible array of facilities, making our innovative human centred computing research possible.
We are treating technology less as a tool, and more as a collaborator. In the move towards more sophisticated automation it is increasingly important that everything we design - from cars to personal assistants to algorithms - has human understanding, behaviour and ethics at its centre.
In the Department of Computer Science, human centred computing researchers are working in diverse fields including healthcare, robotics, virtual reality, media and beyond, to pioneer new forms of technology that will transform our lives, in exactly the ways we want them to.
Areas of expertise
Our researchers focus their work in the following specialist areas:
-
Human computer systems
Understanding how humans use and interact with computing systems is critical, and part of our core mission. We blend expertise in interface design with psychology theories, to build more intuitive computing systems.
Read more
-
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.
Read more
Postgraduate research projects
Human centred computing projects
- "A la carte": multimodal development of tailored dashboards
- Arousal and Scanpath Trend Analysis (a-STA)
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Digital Multimedia and Human Memory
- Evaluating Systems for the Augmentation of Human Cognition
- Machine Learning and Cognitive Modelling Applied to Video Games
- Pervasive Technology for Multimodal Human Memory Augmentation
- Smart Security for Smart Services in an IoT Context
- Social Human-Robot interaction using visual object recognition and hand pose estimation
- Type 1 Diabetes: Accurate Prediction of Glucose Absorption from Food
- Web Users with Cognitive Disabilities: Interaction Differences and Coping Strategies
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
Sarah Clinch projects
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