Data Intensive Science is a rapidly emerging, cross disciplinary research challenge already traversing the fields of Materials Science, Bio-medical research, Computational Engineering and Digital Humanities (to name a few). With huge volumes and complex data at the heart of many research projects, advancing the methods used to analyse, manage, and interpret this data is key to facilitating both efficient and reliable science.

The significance of the discipline has recently been recognised by the Engineering and Physical Sciences Research Council (EPSRC) in awarding £20 million to 6 new national supercomputing centres, including the Cambridge Centre for Data Driven Discovery. This event aims to bring together researchers from varying disciplines across SES and provide them with a forum to share ideas, discover cross-disciplinary patterns in data intensive research, and solve larger research problems.

This event was hosted by King’s College London and the Science and Engineering South Consortium (SES) and open to researchers, support staff, academics and industry members from across King’s College London, the SES Consortium, and the UK.

From our last event

Guest Post: Inspiring New Science

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Lei Tan is a PhD student from Queen Mary University of London under the guidance of three supervisors: Prof. Martin Dove, Dr Andrei Sapelkin and Dr Alston Misquitta. She is currently studying the structure of metal chalcogenide nanoclusters, in particular a group called magic-size clusters that have an extremely small size (knowledge of their structures at an atomic level is critical for further understanding).  In her work, Tan combines experiment methods (xray total scattering, neutron scattering) and simulation (DFT and Reverse Mont-Carlo modelling), requiring large amounts of CPU time. She is one of the pilot users of the Thomas supercomputer. I...
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“most enjoyed the influence of AI in modern and future science”

“thank you for organising the excellent event”

“All of the afternoon’s talks were related in some way to my research and greatly inspired me”

Prof. Franca Fraternali

Big Data Challenges in Biology and Medicine, KCL/CRICK

Prof. Tim Hubbard

HPC Environments for Genome/Phenome Analysis within Health Systems, KCL

Dr. Mark Coté and Dr. Tobias Blanke

Big Data in Culture and Society, KCL

Prof. John Polak

Digital Innovation in Cities, Imperial College London

Dr. Ariana Fornili

Computational Modelling of Protein Dynamics in Heart Disease, QMUL

Panel Session led by Dr. Jacky Pallas

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