Other Cambridge events

Big Data and scientific research: the very small, the fairly big and the massive

Please note this venue is mostly accessible but has one step when first entering.
Past event - 2018
Mon 14 May Doors open at 18:30
Start time 19:00
End time 21:30
Panton Arms, 43 Panton Street,
Cambridge CB2 1HL
Sold Out!
Data mining and analytics have hit the news recently with concerns about social media and privacy, but across many scientific disciplines Big Data is revolutionising research with incredible potential to transform our understanding of the world and beyond. Our speakers will guide us through their big data projects, involving the cells that make up our bodies, the causes of extreme climate events and the stars in our universe. Please note that although this event takes place on the ground floor, there is no step-free access or disabled toilet at the venue.

The Human Cell Atlas - Google Maps for Human Anatomy

Laura Clarke (Project Coordinator - Human Cell Atlas, EMBL-EBI)
Advances in technology mean that we can now analyse single cells in unprecedented detail. The Human Cell Atlas is an ambitious collaborative project that aims to to map all cells in the human body. This talk will introduce the project itself, the technology it will use to analyse our cells and the software platform being built to support producing a 'Google Maps' for the human body.

Climate Prediction in the Big Data Era

Scott Hosking (Climate Scientist, British Antarctic Survey)
The increasing severity and frequency of high-impact weather events means more of us are living under the threat of flooding, heat waves, or drought. To increase our resilience to these events, there is an urgent need to make regional climate predictions more useful and actionable. In this talk I will discuss ways in which machine learning can help unlock the potential within the vast volumes of environmental data available.

Cosmology and Big Data

James Fergusson (Centre for Theoretical Cosmology Lecturer and Deputy Director of the Centre for Doctoral Training in Data Intensive Science)
Up until 2001, cosmology was an imprecise science, data sets were limited and most insights gained from them were qualitative; a successful theory needed only to fit within the right order of magnitude. This changed with the WMAP measurement of the cosmic microwave background radiation, shunting cosmology into a quantitative era where now predictions have to agree at the percent level. In this talk I will introduce the standard cosmological model, discuss how cosmology has evolved into a data driven science, and how it will have to change in the future for vast experiments.
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