Proud to announce the official launch of the Young Scientists’ universal Code of Ethics for Researchers. May the Code be a valuable guide on your journey to scientific discoveries!
Events
Medical Imaging meets NIPS 2017
We held a successful workshop on Medical Imaging meets NIPS in Long Beach, USA. Recorded invited talks can be found on the workshop website.
Talk at Deep Learning in Healthcare Summit
I had the pleasure to speak again at the 2017 Deep Learning in Healthcare Summit 2016 in London.
Video Lectures of MISS 2016
The recorded lectures of the Medical Imaging Summer School 2016 are now available online.
World Economic Forum 2016
I had the great pleasure to speak at the World Economic Forum’s Annual Meeting of the New Champions in Tianjin, China. A more detailed news item can be found on Imperial’s website and in the latest Imperial podcast.
Demo at Imperial Festival 2016
We had great fun at Imperial Festival 2016 demonstrating joint work with Phil Noonan from Imanova on head tracking for motion compensation in medical imaging.
Invited talk at the Deep Learning in Healthcare Summit 2016
I had been invited to speak at Deep Learning in Healthcare Summit 2016 held in London.
NVIDIA Global Impact Award Finalists
We are very excited to be placed among five finalists for the 2016 NVIDIA Global Impact Award with our work on Deep Learning for Brain Lesion Segmentation. The credit goes to PhD student Konstantinos Kamnitsas. More details about the work can be found here.
Invited talk at Big Data, Multimodality & Dynamic Models in Biomedical Imaging Workshop
I had the pleasure to give an invited talk at a workshop organised by the Turing Gateway to Mathematics on Big Data, Multimodality & Dynamic Models in Biomedical Imaging. The talk on Machine Learning for Medical Image Analysis was recorded and is now available online.
Video Lectures of the 2015 Biomedical Image Analysis Summer School
The recorded lectures of the 2015 Biomedical Image Analysis Summer School are now available on YouTube, including my own presentation on Random Forests in Medical Image Analysis.
