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Department of Computer Science

Abstract connections of lines and spheres

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:

  • A collection of test tubes

    Bio-health informatics

    We are designing future technologies to revolutionise healthcare: from modelling biological processes to developing learning health systems, from low-energy sensors to harnessing multi-modal patient's data.

    Contact: Robert Stevens

  • Man looking serious as he uses his laptop

    Data security and privacy

    Data security and privacy is of paramount importance. People generate, process and share more personal data than ever before, and need protection. We analyse and design advanced cryptographic protocols that offer 'security-by-design' and 'privacy-by-design' in various real-world application areas, including e-banking, e-health, connected cars, smart grid and smart cities.

  • Visual representation of data

    Description logics

    Description logics are a well-known family of logics for knowledge representation that are used as logical underpinning of modern ontology languages, in particular OWL. We investigate various reasoning problems, including subjective ones like modularity, learning ontologies from data.

    Contact: Uli Sattler

  • A robot operating a Rubik's Cube

    Machine learning

    Machine learning is revolutionising the world. No other technology is progressing so rapidly in terms of real-world impact. We make world-leading contributions with new theory, methodologies and cross-discipline scientific impact, as well as consumer-driven applications.

    Contact: Gavin Brown

  • Picture of skull CT scan on the wall

    Medical imaging

    Modern technology (X-rays, CT scans etc) can look inside the body, but radiologists are overwhelmed with the huge variety and number of images that are being taken. We are developing software to measure organs, locate abnormalities and diagnose diseases.

    Contact: Tim Cootes

  • Man looking at visual data

    Ontologies and metadata

    Ontologies capture rich domain knowledge for intelligent applications and metadata. They enable a shared understanding of relevant terms in a domain, eg biology of healthcare between different users and computer applications. We are leaders in fundamentals, applications and more.

    Contact: Uli Sattler

  • Hand pressing option on walled touch screen

    Text mining

    The vast majority of information is in free text form. From theoretical modelling of language to large-scale processing of social media and literature to mitigating information overload and overlook, we are enabling computers to use natural languages like we do.

    Contact: Goran Nenadic

Postgraduate research projects

Data science projects

Richard Banach projects

Ke Chen projects

Angelo Cangelosi projects

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

Sandra Sampaio projects

Carole Twining projects

Markel Vigo projects