Data science
Data 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 fons-datascience-PQ@groups.imperial.ac.uk.
Theme leads
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Guy Nason
About
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.
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Sophia Yaliraki
About
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
Support with your grant research proposal
If you need support with your grant proposal writing, please complete the FoNS Research Grant Proposal Support Form. This will allow the strategic research team to understand the type of support you need before they contact you.
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 a.heavens@imperial.ac.uk
Data science theme activities
FoNS Data Science theme Ambassadors - check the news story!
Ioanna Papatsouma (Teaching Fellow in Statistics), Steven Bennett (Chemistry Research Postgraduate) and Elizaveta Semenova (Research Associate in Mathematics) have been selected to foster connections and organise activities across FoNS departments in the area of data science, aimed at early career researchers (ECRs).
Building a career: in and around data science (28 April 2021) - watch it again!
The FoNS Data Science theme champions, Professors Sophia Yaliraki and Guy Nason, hosted a panel to discuss what it takes to become a research leader in this area. Chaired by Guy, and aimed at early career researchers in the Faculty of Natural Sciences, our panel told the audience about their journeys in data science, took part in a Q&A and concluded with tips for navigating this kind of career path.
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.