I am a Lecturer (roughly equivalent to Assistant Professor) in Machine Learning at the University of Glasgow. My research focuses on building machines that understand the visual world with minimal supervision, learning aspects of its structure such as 3D geometry and decomposition into objects. This work lies at the intersection of machine learning, computer vision, and computer graphics. I also work on applications of machine learning and computer vision in the physical and life sciences.
Prospective PhD students: I am currently accepting PhD students to supervise. There are studentships available for strong candidates. Please first check that your research interests align with mine (read this page; read some of my papers). If so, send me an email with your CV, transcripts and a short research proposal (2–3 pages) mentioning why you want to work in my group in particular, and what skills make you suited. Note that I expect students to produce at least two 'good' papers during their PhD (CVPR, NeurIPS, etc.). Applicants should have a strong background in coding and maths (e.g. probability, linear algebra).
I completed a BA in Mathematics at the University of Cambridge in 2009, followed by an MSc in Informatics at the University of Edinburgh in 2010. I then worked at Blackford Analysis for four years, on research and development for medical imaging applications. I completed my PhD in 2018 at the University of Edinburgh in the CALVIN group supervised by Vittorio Ferrari (see here for my thesis). I spent three years as a postdoc in the Computer Vision and Machine Learning Group of Christoph Lampert at ISTA, the Institute of Science and Technology Austria. Since January 2022, I hold the post of Lecturer in Machine Learning, in the School of Computing Science at the University of Glasgow. My 'official' (not-so-interesting) homepage is here.
My curriculum vitae is available here.