Dr Paul Henderson
- Lecturer in Machine Learning (School of Computing Science)
I hold the post of Lecturer in Machine Learning, in the School of Computing Science at the University of Glasgow, since January 2022. Previously, 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.
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.
- Royal Society Research Grant, 2022-2023 (£20K; sole PI)
I am currently accepting PhD students to supervise. Possible topics include deep generative models, applications of machine learning in the sciences and computer graphics, and other areas within machine learning and computer vision.
If you want to apply, please first check that your research interests align with mine (read some of my papers!). If so, send me an email with your CV 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).
- Chaichakan, Tanatta
Weakly-supervised learning for medical image understanding
- Fan, Shiyu
Reconstructing Physcially Feasible 3D Human Model in Close Human-Human and Human-Object Interactions from Monocular Images
- He, Zhuo
Generalized Machine Learning with limited Training Data
- Liu, Qianying
Deep Learning for Health Informatics
- Shi, Tong
Deep Learning based Audio-Visual Emotion Recognition to Enhance Human-Robot Interaction
- Sivangi, Kaushik Bhargav
Human Motion Analysis for Healthcare Applications
- Xu, Wenning
Modelling Two-person and Human-object Close Interactions
- CS5002 Advanced Programming
- CS4061 Machine Learning
Google Scholar: https://scholar.google.co.uk/citations?user=HN7fd4MAAAAJ