Research projects
Find a postgraduate research project in your area of interest by exploring the research projects that we offer in the Department of Computer Science.
We have a broad range of research projects for which we are seeking doctoral students. Browse the list of projects on this page or follow the links below to find information on doctoral training opportunities, or applying for a postgraduate research programme.
Alternatively, if you would like to propose your own project then please include a research project proposal and the name of a possible supervisor with your application.
Available projects
Deep Learning for Temporal Information Processing
Primary supervisor
Additional information
Contact admissions office
Other projects with the same supervisor
- Automatic Emotion Detection, Analysis and Recognition
- Biologically-Plausible Continual Learning
- Zero-Shot Learning and Applications
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Multi-task Learning and Applications
- Explainable and Interpretable Machine Learning
- Machine Learning and Cognitive Modelling Applied to Video Games
- Automatic Activity Analysis, Detection and Recognition
- Music Generation and Information Processing via Deep Learning
- Contextualised Multimedia Information Retrieval via Representation Learning
Funding
- Competition Funded Project (Students Worldwide)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.
Project description
Temporal information process covers a broad class of learning problems where knowledge can be acquired from data of a sequential order, e.g. speech modelling, image sequence analysis, robot navigation, financial prediction, and so on. In addition, different learning paradigms, supervised, unsupervised, and reinforcement styles, may be involved in temporal information processing. Recent studies suggested that deep learning has several advantages for temporal data analysis and information extraction regardless of a learning paradigm and can overcome a number of weaknesses of existing temporal information processing methods.
In this project, the following issues will be investigated: 1) Exploration of novel deep architectures for effective encoding temporal information, 2) Model selection issues in the context of the hybrid learning strategy for different learning paradigms, 3) Highly non-linear temporal coherence/factor analysis with different strategies, and 4) Applications in selected real world temporal information processing tasks, e.g., audio stream analysis and financial/stock data mining. In general, this project is suitable for one who is interested in fundamental research in machine learning while it is acceptable for one who has a relevant application problem in mind and wishes to tackle their problems with an emerging technology such as deep learning.
In order to take this project, it is essential to have good background knowledge in mathematics, machine learning as well as good programming skills. If you are interested in this project, please first visit my research student page: http://staff.cs.manchester.ac.uk/~kechen/ for the required materials and information prior to contacting me.
Person specification
For information
- Candidates must hold a minimum of an upper Second Class UK Honours degree or international equivalent in a relevant science or engineering discipline.
- Candidates must meet the School's minimum English Language requirement.
- Candidates will be expected to comply with the University's policies and practices of equality, diversity and inclusion.
Essential
Applicants will be required to evidence the following skills and qualifications.
- This project requires mathematical engagement and ability substantially greater than for a typical Computer Science PhD. Give evidence for appropriate competence, as relevant to the project description.
- You must be capable of performing at a very high level.
- You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.
Desirable
Applicants will be required to evidence the following skills and qualifications.
- You will have good time management.
- You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
General
Applicants will be required to address the following.
- Comment on your transcript/predicted degree marks, outlining both strong and weak points.
- Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
- How well does your previous study prepare you for undertaking Postgraduate Research?
- Why do you believe you are suitable for doing Postgraduate Research?