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Department of Computer Science

Representation Learning and Its Applications

Primary supervisor

Additional information

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Other projects with the same supervisor


  • 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

Representation learning aims at extracting refined information from raw data, and encoding it by data representation with low memory usage, which needs to be sufficiently accurate for further use in pattern recognition, prediction and exploration tasks. This project invites PhD candidates who are interested in this particular topic and its applications.

You will be focused on one of the following directions:

* Data visualisation by learning data representations in 2D or 3D space to facilitate data understanding based on visual observation.

* Representation learning for special type of data, e.g., relation data (e.g., knowledge graphs, networks and ratings), symbolic data (e.g., logic expressions), sequential data (e.g., signals), by constructing point coordinates, geometric shapes and probability distributions in low-dimensional space.

* To leverage multimodal data collected from different information resources, or to leverage data and knowledge.

The research will be supported by linear algebraic, geometric, probabilistic and optimization theories. The focus can be either on novel algorithm design, efficient optimization, establishing theoretical understanding, or large-scale domain specific applications (e.g., bio, scientific, health data).

We will consider applicants who have:
* Very strong interest in the above research fields.
* An excellent undergraduate degree in Computer Science or Mathematics (or related discipline), and preferably, a relevant M.Sc. degree.
* Very good experience with computer programming of mathematical models and algorithms (in Matlab, R or Python, or other platforms).
* Excellent report writing and presentation skills.
* Excellent ability to communicate with fellow students and colleagues.

Please, note that applicants are preferably to have a first-class (or an equivalent international qualification) degree, and must additionally satisfy the standard requirements for postgraduate studies at the University of Manchester, such as English language qualifications, as stated in the PGR guidelines.

Qualified applicants are strongly encouraged to informally contact the supervising academic Dr. Tingting Mu ( to discuss the application and possible research titles prior to applying.

Person specification

For information


Applicants will be required to evidence the following skills and qualifications.

  • 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.


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.


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?