Recent News

Mar2018 PhD Opportunities! I have two open funded PhD opportunities for UK/EU students.
The first is on Uncertainty Quantification for Data Efficient Machine Learning and is sponsored by the National Physical Laboratory; further details and application link avaiable here.
The second is on Real-Time Semantic Depth Layer Decomposition for Augmented Reality in collaboration with Ed Rosten at SnapChat Research (London) and Christian Richardt; further details and application link avaiable here.
Mar2018 Post Doctoral Research Opportunity! We are now hiring for a three year Computer Vision position to extend our recent research in Bayesian deep learning with the goal of automated diagnosis of Malaria. More details can be found here and the application website is here.
Mar2018 I will be giving a talk about Probabilistic Generative Models at the BMVA Summer School as well as taking a lab on Python and TensorFlow for Computer Vision.
Feb2018 Our papers on Structured Uncertainty Prediction and Diverse Networks have been accepted to CVPR 2018. The papers are now available here and here.
Jan2018 We will be starting work on a new Global Challenges Research Fund project, led by Richard Bowman, on using machine learning and computer vision to automate the diagnosis of Malaria from low cost 3D printed microscopes! Further details of research positions will be advertised soon.
Dec2017 I was general chair of CVMP 2017 and would like to thank all the committee, keynote speakers, contributors and attendees from both academia and industry for making an interesting, thought-provoking and enjoyable conference.
Nov2017 Our papers on Nonparametric Inference for VAEs and Latent Structure Learning have been accepted to the NIPS workshops on Advances in Approximate Bayesian Inference and Advances in Modelling and Learning Interactions from Complex Data. The papers are now available here and here.
Oct2017 Our paper on laplacian pyramid conditional VAEs has been accepted to CVMP 2017. The paper is now available.
Jun2017 I have been awarded a Royal Society Industry Fellowship to work in collaboration with the Foundry on a four year project developing Intelligent Tools for the Creative Industries.

Visual Computing and Machine Learning

Welcome to my website. I am a Royal Society Industry Fellow and work in the Department of Computer Science at the University of Bath as a Senior Lecturer (Associate Professor) in Computer Vision, Graphics and Machine Learning. I also hold an Honorary Lecturer position in the Virtual Environments and Computer Graphics Group in the Department of Computer Science at University College London where I was formerly a Research Associate working with Jan Kautz and Simon Prince on synthesizing and editing photorealistic visual objects funded by the EPSRC.

My main area of research involves learning models of shape (2D and 3D) and appearance from images. In particular, I am interested in performing this in an automatic or interactive fashion that allows these technologies to be put to use in a variety of applications without requiring users to have computer vision or graphics expertise. Further details may be found here as well as in my publications.

Previously I was a Research Associate in the Computer Vision Group of the Machine Intelligence Laboratory, in the Department of Engineering at the University of Cambridge working on the EU Hydrosys Project led by Ed Rosten. I completed my PhD, in the Computer Vision Group at the University of Cambridge, under the supervision of Roberto Cipolla and the guidance of George Vogiatzis and Carlos Hernández. I was funded by a Schiff Foundation Scholarship and Toshiba Research.