Projects per year
Personal profile
Research interests
I am a Royal Society Industry Fellow and Professor of Visual Computing and Machine Learning in the Department of Computer Science. I am the Director of the CAMERA research centre and work with the Visual Computing Group as well as serving as co-director of the university's research centre in Mathematics and Algorithms for Data.
I am interested in the modelling of shape and the use of machine learning techniques applied in the domain of computer vision (processing images from the real world) and graphics (creating and manipulating new images). Shape is such a fundamental component of graphics and vision that research in this field unifies the two subjects and there is obviously a great advantage to solving problems in both areas simultaneously since they help one-another. My latest ongoing research aims to learn automatically models of both man-made and natural shapes, and produce intelligent systems that make it easier to process, create and manipulate images. For further details please see my personal homepage for further details and publications.
Willing to supervise doctoral students
Please see the link here for details on open PhD and PostDoc positions in my group.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Engineering, Doctor of Philosophy, Automatic 3D Model Acquisition from Uncalibrated Images, University of Cambridge
2006 → 2010
Award Date: 14 May 2011
Engineering, Master of Engineering, University of Cambridge
2002 → 2006
External positions
Honorary Associate Professor, University College London
2018 → …
Royal Society Industry Fellow, The Royal Society
2017 → …
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
-
Ensuring Data Privacy in Deep Learning through Compressive Learning
Nunes, M., Campbell, N., Poon, C. & Chen, C.
Engineering and Physical Sciences Research Council
1/04/23 → 31/03/24
Project: Research council
-
EMIL: The European Media and Immersion Lab (Former EU Project)
Lutteroth, C., Campbell, N., Clarke, C. & O'Neill, E.
1/09/22 → 28/02/25
Project: EU Commission
-
My World - Strength in Places Fund
Cosker, D., Campbell, N., Li, W. & Stanton Fraser, D.
1/04/21 → 31/03/26
Project: Central government, health and local authorities
-
Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) - 2.0
Cosker, D., Bilzon, J., Campbell, N., Cazzola, D., Colyer, S., Lutteroth, C., McGuigan, P., O'Neill, E., Petrini, K., Proulx, M. & Yang, Y.
Engineering and Physical Sciences Research Council
1/11/20 → 31/10/25
Project: Research council
-
Machine Learning tools for Healthcare and Sports Performance Applications
Project: Research-related funding
Research output
-
Regularising Inverse Problems with Generative Machine Learning Models
Duff, M., Campbell, N. & Ehrhardt, M. J., 9 Oct 2023, (E-pub ahead of print) In: Journal of Mathematical Imaging and Vision .Research output: Contribution to journal › Article › peer-review
Open Access -
VAEs with structured image covariance applied to compressed sensing MRI
Duff, M. A. G., Simpson, I. J. A., Ehrhardt, M. J. & Campbell, N. D. F., 3 Aug 2023, In: Physics in Medicine and Biology. 68, 16, 165008.Research output: Contribution to journal › Article › peer-review
Open Access -
Aligned Multi-Task Gaussian Process
Mikheeva, O., Kazlauskaite, I., Hartshorne, A., Kjellström, H., Ek, C. H. & Campbell, N., 28 Mar 2022.Research output: Contribution to conference › Paper › peer-review
File43 Downloads (Pure) -
Aligned Multi-Task Gaussian Process
Mikheeva, O., Kazlauskaite, I., Hartshorne, A., Kjellström, H., Ek, C. H. & Campbell, N. D. F., 30 Mar 2022, Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS). Camps-Valls, G., Ruiz, F. J. R. & Valera, I. (eds.). Vol. 151. p. 2970-2988 19 p. (Proceedings of Machine Learning Research).Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding
Open Access -
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching
Chen, C. & Campbell, N., 24 Nov 2022.Research output: Contribution to conference › Paper › peer-review
Open Access