AI and Big Data - The Bloomsbury Set

AI and Big Data

The utilisation of AI and Machine Learning to tackle infectious diseases and AMR challenges was explored by interdisciplinary teams during two face-to-face events. Projects were selected by participants pitching their ideas to a panel of ‘Dragons’. Eight projects were awarded £2,000 at the first stage and additional £30,000 was awarded in the second round for five of these projects to develop their proposed innovative solutions.

Building automated genomics data curation and collection pipeline

Dr Jody Phelan (LSHTM), Gary Napier (LSHTM), Dr Ruby Chang (RVC) and Dr Martin Walker (RVC) - £30,500

1 October 2019 to 31 March 2021 (Data Grant BSA33)

Machine learning to combat AMR through the integrated analysis of VetCompass and laboratory data

Prof David Brodbelt (RVC), Prof Yonghong Peng (University of Sunderland), Mr Noel Kennedy (RVC), Dr Dan O’Neill (RVC), Dr Collette Taylor (RVC), Prof David Church (RVC) and Dr Sam Clifford (LSHTM) - £30,000

1 October 2019 to 31 March 2021 (Data Grant BSA30)

Phenotype Image Data and Digital Learning Innovation (PhIDDLI)

Dr Michael Delves (LSHTM), Dr Rajat Dhawan (LSE), Dr Maurizio Gioli (SOAS) and Dr Edgar Whitley (LSE) - £32,000

1 October 2019 to 31 March 2021 (Data Grant BSA28)

Big data analysis to identify innovative solutions for combating respiratory disease and reducing antimicrobial use in beef cattle

Prof Luca Guardabassi (RVC), Dr Richard Stabler (LSHTM), Dr Muna Anjum (APHA) and Prof Debby Bogaert (University of Edinburgh - £32,000

1 October 2019 to 31 March 2021 (Data Grant BSA27)

Predicting treatment outcomes for neglected tropical diseases

Dr Martin Walker (RVC), Dr Jody Phelan (LSHTM) and Dr Julie Halder (RVC/IDDO) - £31,220

1 October 2019 to 31 March 2021 (Data Grant BSA34)