Participated in the Three Minute Thesis (3MT) Competition at TUM

On 20 January 2017 I took part in the Three Minute Thesis (3MT) competition for doctoral candidates of the Technical University of Munich, held at the TUM Institute for Advanced Study as part of the symposium of the BERTI training network and announced by the TUM Graduate School. Each candidate had three minutes and a single slide to explain their research to a general audience; first prize was a research travel grant of up to €1,000.

My three minutes were about my PhD research on learning from crowds: how annotations collected from many non-experts, through crowdsourcing and games (“playsourcing”), can train deep learning models for medical images, as in our AggNet and playsourcing papers.