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 - Champion
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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 - Champion
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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.
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Steven Bennett - Ambassador
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About
Steven is a PhD student in the Jelfs group in the chemistry department and is interested in the application of machine learning for the discovery of new materials. Working at the interface between different fields, he is interested in how data science tools can help enhance his own research and how they can accelerate the discovery of new materials to tackle global challenges
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Ioanna Papatsouma - Ambassador
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About
Ioanna is a Teaching Fellow in Statistics in the Department of Mathematics, striving to improve the quality of statistics education at Imperial. Her research interests lie broadly in the area of clustering; particular areas of focus include the development of clustering mixed-type data, constrained clustering and robust clustering.
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Elizaveta Semenova - Ambasssador
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About
Elizaveta (aka Liza) is a Postdoctoral Research Associate at the University of Oxford in the Department of Computer Science. She works on scalable and flexible methods for modelling of spatiotemporal data. Her research spans such fields as spatiotemporal statistics, Bayesian machine learning, epidemiology and public policy. Currently, she is focusing on adaptive survey design methodology, as well as using deep generative modelling to power MCMC inference in classical spatial statistics. She is passionate about community building and creation of equitable opportunities in Data Science for people of all backgrounds.
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.
Data science theme activities
Data Science Theme Industry Showcase (24 October 2022) - check the news story!
A half day of presentations and lively discussions took place on 24 October as part of the data science theme industry showcase. Hosted by the FoNS Data Science theme and Imperial-X (I-X), the event brought together a diverse range of industry contacts and cross-College group of researchers
Meet our Ambassadors! (10 May 2022) - check the news story!
IMSE and DigiFAB Datathon held their first joint datahon four multidisciplinary teams of students and early career research graduates competed on the 27th and 28th April 2022. The Faculty of Natural Sciences Data Science Champions (Professor Sophia Yaliraki and Professor Guy Nason) and also the Data Science Ambassadors (Steven Bennett and Elizaveta Semenova) welcomed all participants and helpers to a wonderful event in the Physics Common Room. This event gave those who joined virtually the chance to meet in person and discuss how they approached the challenge. A few short presentations from the winning teams were made and they each asked questions on their methods and results.
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.