
Lightweight U-Nets: Efficient CNNs for fast medical image analysis
Work conducted during my time at the Machine Learning in Neuroimaging Lab in the IBME, Univeristy of Oxford
Sagar Vaze
Machine Learning and Computer Vision
PhD Student at Oxford University
Working in the Visual Geometry Group
I'm a third year PhD student in the Visual Geometry Group at Oxford University, co-supervised by Prof. Andrew Zisserman and Prof. Andrea Vedaldi. I previously studied Engineering Science, also at Oxford, graduating in 2018. In between graduating and beginning my PhD, I was fortunate to work at CuriousAI in Helsinki (now acquired by Apple) and Founders Factory in London. I have since continued to work with start-ups when time allows. My research is funded by a Facebook AI Research Scholarship.
Work conducted during my time at the Machine Learning in Neuroimaging Lab in the IBME, Univeristy of Oxford
My research focuses on Open World Learning - I am interested in learning representations from limited (labelled) training sets which can generalize to 'open world' data, where the data distribution (e.g categories or domain) may be different.