|Chris G. Willcocks
Department of Computer Science
Office: MCS 2026
My research spans a number of areas in computer science, including machine learning, computational geometry and generative models. Here is a list of my publications and a link to my scholar. For recent news please visit my twitter profile, and for software updates visit my github page.
- Bond-Taylor, S., Leach, A., Long, Y., & Willcocks, C. G. (2021). Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1–1. doi:10.1109/TPAMI.2021.3116668
- Ramaswamy, V. K., Musson, S. C., Willcocks, C. G., & Degiacomi, M. T. (2021 , Mar). Deep Learning Protein Conformational Space with Convolutions and Latent Interpolations. Phys. Rev. X, 11, 011052. doi:10.1103/PhysRevX.11.011052
- Bond-Taylor, S., & Willcocks, C. G. (2021). Gradient Origin Networks. International Conference on Learning Representations (ICLR). URL: https://openreview.net/pdf?id=0O_cQfw6uEh
- Leach, A., Schmon, S. M., Degiacomi, M. T., & Willcocks, C. G. (2022). Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment. ICLR 2022 Workshop on Geometrical and Topological Representation Learning. URL: https://openreview.net/forum?id=BY88eBbkpe5
I teach the year three deep learning and reinforcement learning modules, alongside the year two ‘cyber security’ submodule. Slides and other material are available in the teaching section. Past teaching:
- Deep Learning (2019-present)
- Reinforcement Learning (2020-present)
- Cyber Security (2017-present)
- Machine Learning (2018)
I am an Assistant Professor in Computer Science at Durham University and a member of the Innovative Computing Group (ICG). I cofounded the research spinout company Intogral Limited which deploys deep learning models in the area of medical image computing. Previously I worked as a PDRA for Newcastle University, Durham University, and have been a visiting scholar at both the Chinese University of Hong Kong (CUHK) and the Hong Kong University of Science and Technology (HKUST). My interdisciplinary research focuses on providing elegant solutions to computationally expensive or ill-defined problems within the fields of computational geometry, cyber security, machine learning, medical image computing and biophysics.
- Invited speaker at BMVA 2022 Summer School (slides).
- Admissions tutor (2021-present).
- Open Day coordinator (2021-2022).
- Area Chair of BMVC 2021.
- Invited speaker at 2020 Cyber Operational Conference on ‘Meta learning: Smart Interfacing’.
- Area Chair of BMVA 2020 Conference.
- Participating scientist on Scientist Next Door (SND).
- Invited speaker at Chinese University of Hong Kong (CUHK), 13th Aug 2019.
- Chair of BMVA symposium of ‘Deep Learning in 3-Dimensions’, 20th Feb 2019.
- Speaker on BBC Sunday Politics discussing Cyber Security spending in public bodies.
- Invited to present at Durham Celebrating Excellence research exhibition.
- Member of W3C Web Assembly.
- Reviewer for CVPR.
- Reivewer for IEEE Transactions on Information Forensics & Security.
- Reivewer for IEEE Transactions on Medical Imaging.
- Reivewer for IEEE Transactions on Image Processing.
- Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Reviewer for IEEE Transactions on Neural Networks and Learning Systems .
- Reviewer for Journal of Real-Time Image Processing
- Currently pursing Fellowship in HEA through PGCLTHE course.
- Member of Scientific Computing research group.