Data visualisation wall in the Data Science InstituteData science is all-pervasive in most disciplines and based on foundations in a number of areas including mathematics, computer science, artificial intelligence and statistics.

Our data science theme is intended to bring together those interested in data science, constituencies that are producers/developers of data science methods, those who are users of innovative methods and those that do both. Our theme intends to provide a networking hub, training opportunities and events.

Our key focus is to foster improved research and help put in place structures to increase resourcing for that research. This will include a focus on grant-getting, industrial collaboration and improving mobility of personnel to enable technology transfer of data science technology across the Faculty.

Theme leads

Get in touch with the theme members by emailing

Theme leads

  • Guy Nason

    Guy Nason

    Personal details

    Guy Nason Chair in Statistics


    Guy is interested in all areas of statistics and machine learning, particularly in time series and networks, ethics in data science, with applications in official and government statistics. He currently teaches a new third-year undergraduate course on statistical learning.

  • Sophia Yaliraki


    Personal details

    Sophia Yaliraki Professor of Theoretical Chemistry


    Sophia Yaliraki is Professor of Theoretical Chemistry. Her group and collaborators develop multiscale techniques based on graph learning with applications in Precision Healthcare, Digital Chemistry, Computational social science and Online learning analytics. She teaches Data Analytics in Chemistry.

Coordinating research activities

Internal funding opportunities

Funding to Support Proposal Development in the Area of Data Science - Call for Expression of Interest Round 2

We are inviting 2-page Expressions of Interest for internal funding that can be used to support the writing and submission of large-scale and multidisciplinary grant proposals.

Funding available: Up to £6,000 per proposal is available to support the salary costs for grant writing or undertaking work essential for the preparation of the full proposal.

Deadline: All applications should be sent to Sophie Armstrong-Brown by Friday 16th April 2021 5pm. Find out more about guidance and deadlines for this call (only FoNS staff).

Any questions, please contact the Faculty Theme Champions, Sophia Yaliraki and Guy NasonSophia and Guy will be available to discuss this opportunity and potential Big Ideas on Friday 9th April 2021 at 2pm. Use the link provided below to join the MS Teams meeting. Click here to join the meeting

Supported proposals

Title of the proposal: Big Data and Machine Learning in the Natural Sciences 

Extensive expertise and activity in machine learning (ML), AI and data analysis techniques exist in the Faculty, e.g. statistical inference and landscape scanning in astrophysics, particle physics, theoretical physics, climate modelling, nanophotonics, properties of materials and drug discovery, real-time analysis of large data volumes in chemistry and physics, ML in statistical analysis in physics and mathematics.  This Faculty-wide forum/network, with seminars and workshops, will give opportunities for better coordination and collaboration within and indeed beyond the Faculty, through sharing of ideas and best practice and even a common tool base. Such a forum can also serve as incubator for multidisciplinary funding ideas, linked by a common ML aspect. For further information, or if you want to be involved, please contact Professor Alan Heavens at

Data science theme activities

Building a career: in and around data science (28 April 2021)

Sophia Yaliraki and Guy Nason are hosting this panel to discuss what it takes to become research leader in and around the area of data science in a natural sciences context. It is designed to convey the strategies and paths one can take rather than the details about the science. Expect to hear about professional development opportunities, working with other scientists and networking, fostering an equal, diverse and inclusive environment, working within the UK research ecosystem and with industry and government, the grant programme landscape, what kinds of outputs (publications) to aim for, data ethics, and other `tricks of the trade’. See details and how to register to this event in the College events webpage.

DigiFAB datathon (24 March 2021) - check the news story!

The Digital Molecular Design and Fabrication (DigiFAB) Institute and the FoNS Data Science Theme invite third- and fourth-year undergraduate students, postgraduate taught and research students, postdocs and early career researchers interested in the area of Data Science to participate in this free datathon. Find out more about the event.

If you want to know how to make a virtual multidisciplinary datathon happen - check out this article published in the May FoNS Newsletter!

Data Science Virtual Poster Competition 2020 - check the news story!

The Faculty of Natural Sciences invited its PhD students, Postdocs, Early career researchers and research groups working on the area of Data Science theme to participate at this virtual poster competition. The judging panel nominated the top two best posters, and in addition the ‘popular choice’ award saw more than 170 Imperial students and staff voting for their favourite poster. Find out who won the competition and view their posters