Gareth Conduit has a track record of applying artificial intelligence to solve real-world problems, with research contracts held with companies spanning from materials science to healthcare. Gareth holds an academic position at the University of Cambridge and is a Fellow of Gonville & Caius College.
Using advanced, proprietary deep learning methods to train from incomplete data and correlate noise
Predicting expensive experimental datapoints using minimal known data combined with larger cheaper datasets
Software that can be used online or embeded within your own platforms and workflows