|Assistant Professor in the Department of Computer Science||MCS 2026||+44 (0) 191 33 44854|
I am an Assistant Professor in Computer Science at Durham University and a member of the Scientific Computing and VIVID groups. My research is in theoretical areas of Deep Learning, specifically looking at Deep Generative Models such as EBMs or with variational Baysian methods. Previously, I co-founded Durham University startup Intogral Limited (now Gliff.ai). Please visit my Website for more information about my research or visit my Google Scholar for a full ist of publications.
Research within my group has led to the invention of Gradient Origin Networks (ICLR 2021), which show that you don't need to use encoders in autoencoders (here is a video by Yannic Kilcher on GONs). We've also published Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models (IEEE TPAMI 2021). We developed an extension of ray tracing for protein docking called Shape Tracing (IEEE BIBE 2020) and an end-to-end solution for Deep Learning Protein Conformational Space (PRX 2021). Our interdisciplinary research has also been applied in unsupervised Medical Anomaly Detection (IEEE ISBI 2021) and in Cross-Domain Imagery (ICPR 2021).
I teach the L3 Deep Learning and Reinforcement Learning module (COMP3547) and the year two Cyber Security submodule (COMP2211). Slides and other material are available in the Teaching section of my website. I also have a YouTube channel with a lot of Deep Learning and Reinforement Learning Material.
I am an Area Chair for BMVC and have been an AC in past BMVA meetings. I've been an invited speaker at several conferences and universities including the 2020 Cyber Operational Conference, and the Chinese University of Hong Kong (CUHK). I was a speaker on BBC Sunday Politics about Cyber Security spending in public bodies, and I am a regular reviewer for IEEE such as IEEE TPAMI, IEEE TIFS, IEEE TNNLS, IEEE TIP and IEEE TMI.
- Innovative Computing
- Isaac-Medina, B.K.S., Bhowmik, N., Willcocks, C.G. & Breckon, T.P. (2022), Cross-modal Image Synthesis in Dual-Energy X-Ray Security Imagery, Proc. Computer Vision and Pattern Recognition Workshops. New Orleans, Louisiana, IEEE.
- Wyatt, Julian, Leach, Adam, Schmon, Sebastian M. & Willcocks, Chris G. (2022), AnoDDPM: Anomaly Detection With Denoising Diffusion Probabilistic Models Using Simplex Noise, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. New Orleans, LA, IEEE, 650-656.
- Leach, Adam, Schmon, Sebastian M., Degiacomi, Matteo T. & Willcocks, Chris G. (2022), Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment, ICLR 2022 Workshop on Geometrical and Topological Representation Learning. ICLR.
- Nguyen, Bao, Feldman, Adam, Bethapudi, Sarath, Jennings, Andrew & Willcocks, Chris G (2021), Unsupervised Region-based Anomaly Detection in Brain MRI with Adversarial Image Inpainting, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). Nice, IEEE, 1127-1131.
- Sunal, Cem Ekin, Willcocks, Chris G. & Obara, Boguslaw (2021), Real Time Fencing Move Classification and Detection at Touch Time during a Fencing Match, International Conference on Pattern Recognition (ICPR). Milan, IEEE, 5760-5766.
- Isaac-Medina, B.K.S., Willcocks, C.G. & Breckon, T.P. (2021), Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery, 25th International Conference on Pattern Recognition (ICPR 2020). Milan, Italy, IEEE.
- Sasaki, H., Willcocks, C.G. & Breckon, T.P. (2021), Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery, 25th International Conference on Pattern Recognition (ICPR 2020). Milan, Italy, IEEE.
- Bond-Taylor, Sam & Willcocks, Chris G. (2021), Gradient Origin Networks, International Conference on Learning Representations. Vienna / Virtual.
- Isaac-Medina, Brian K. S., Poyser, Matthew, Organisciak, Daniel, Willcocks, Chris G., Breckon, Toby P. & Shum, Hubert P. H. (2021), Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark, ICCVW '21. Virtual, Computer Vision Foundation.
- Leach, Adam, Rudden, Lucas S.P., Bond-Taylor, Sam, Brigham, John C., Degiacomi, Matteo T. & Willcocks, Chris G. (2020), Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE). 49-52.
- Jonathan Frawley, Chris Willcocks, Habib Maged, Geenen Caspar, David H.W. Steel & Boguslaw Obara (2020), Segmentation of macular edema datasets with small residual 3D U-Net architectures, IEEE International Conference on BioInformatics and BioEngineering. USA, IEEE.
- Medhat, Fady, Mohammadi, Mahnaz, Jaf, Sardar, Willcocks, Chris, Breckon, Toby, Matthews, Peter, McGough, Andrew Stephen, Theodoropoulos, Georgios & Obara, Boguslaw (2018), TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text, IEEE International Conference on Big Data. Seattle, WA, USA, IEEE.
- Chris G. Willcocks (2013). Sparse Volumetric Deformation - Animating and rendering huge amounts of volumetric data using GPGPU computing. Durham University. PhD.
- Bond-Taylor, Sam, Leach, Adam, Long, Yang & Willcocks, Chris 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
- Ramaswamy, Venkata K., Musson, Samuel C., Willcocks, Chris G. & Degiacomi, Matteo T. (2021). Deep Learning Protein Conformational Space with Convolutions and Latent Interpolations. Physical Review X 11(1): 011052.
- Alhasson, Haifa, Willcocks, Chris G., Alharbi, Shuaa S., Kasim, Adetayo & Obara, Boguslaw (2021). The relationship between curvilinear structure enhancement and ridge detection approaches. The Visual Computer 37(8): 2263-2283.
- Shuaa S. Alharbi, Chris Willcocks, Philip T.G. Jackson, Haifa F. Alhasson & Boguslaw Obara (2019). Sequential graph-based extraction of curvilinear structures. Signal, Image and Video Processing 13(5): 941-949.
- Akcay, S., Kundegorski, M.E., Willcocks, C.G. & Breckon, T.P. (2018). Using Deep Convolutional Neural Network Architectures for Object Classification and Detection within X-ray Baggage Security Imagery. IEEE Transactions on Information Forensics & Security 13(9): 2203-2215.
- Willcocks, Chris G., Jackson, Philip T.G., Nelson, Carl J., Nasrulloh, Amar & Obara, Boguslaw (2019). Interactive GPU Active Contours for Segmenting Inhomogeneous Objects. Journal of Real-time Image Processing 16(6): 2305-2318.
- Nasrulloh, A., Willcocks, C., Jackson, P., Geenen, C., Habib, M., Steel, D. & Obara, B. (2018). Multi-scale Segmentation and Surface Fitting for Measuring 3D Macular Holes. IEEE Transactions on Medical Imaging 37(2): 580-589.
- Willcocks, Chris, Jackson, Philip T.G., Nelson, Carl J. & Obara, Boguslaw (2016). Extracting 3D parametric curves from 2D images of helical objects. IEEE Transactions on Pattern Analysis and Machine Intelligence 39(9): 1757-1769.
- Willcocks, Chris G. & Li, Frederick W.B. (2012). Feature-Varying Skeletonization. The Visual Computer 28(6-8): 775-785.