Our vision is to provide scientists and non-ICT specialists with unprecedented access to cutting-edge Machine Learning algorithms, transforming science across a range of data-intensive disciplines.

By establishing and leading a new theme in ICT research based on Interactive Machine Learning, we are working towards a human-computer interface though which scientists can directly interact with large-scale data and computing resources in an intuitive visual environment.

ENGAGE is supported by an EPSRC grant (ref: EP/K015664/1) as part of the Working Together Programme, and benefits from a number of partnerships.

Updates

We held an ENGAGE Bioacoustics workshop at the University of Warwick – July 2015

Check out our post on automatic bat detection on the Methods in Ecology and Evolution blog.

New paper at CVPR 2015 on machine teaching. See publications.

New paper accepted to PAMI. See publications.

Kate Jones will be on Radio 4′s Inside Science on Thurs 6th March at 4.30pm to talk about big biodiversity data.

Two new papers accepted: bat call classification at AISTATS 2014 and active learning at CVPR 2014. More details to follow.