Staff profile

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. 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 Highlights

Research within my group has led to the invention of Unleashing Transformers (ECCV 2022), which generate diverse high-resolution samples. We also invented 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 published Deep Generative Modelling: A Comparative Review (IEEE TPAMI 2021) with interest in non-adversarial models such a Denoising Diffusion Models for Anomaly Detection AnoDDPM (CVPR NTIRE 2022) and Unpaired Translation UNIT-DDPM. In other domains, 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), Cross-Domain Imagery (ICPR 2021), Multi-view Transformers for Object Detection, and to generate 3D CT-like Images from 2D X-rays MedNeRF (IEEE EMBC 2022).

Teaching

I teach the L3 Deep Learning module (COMP3547), the Reinforcement Learning module 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 Reinforcement Learning Material.

Professional Activities

I am an Area Chair for BMVC and have been an AC in past BMVA meetings. I'm also the Admissions Tutor for Computer Science and in the past have been the Open Day coordinator. 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.

Conference Paper

• Isaac-Medina, B.K.S., Willcocks, C.G. & Breckon, T.P. (2023), Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields, IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023. Vancouver, BC, IEEE.
• Bond-Taylor, S.E., Hessey, P., Sasaki, H., Breckon, T.P. & Willcocks, C.G. (2022), Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes, Proc. European Conference on Computer Vision. Tel Aviv, Israel, Springer.
• Corona-Figueroa, Abril, Frawley, Jonathan, Bond-Taylor, Sam, Bethapudi, Sarath, Shum, Hubert P. H. & Willcocks, Chris G. (2022), MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Glasgow, Scotland, 3843-3848.
• Isaac-Medina, B.K.S., Willcocks, C.G. & Breckon, T.P. (2022), Multi-view Vision Transformers for Object Detection, International Conference on Pattern Recognition. Montreal, Canada, IEEE.
• 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, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 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, 649-655.
• 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.
• Frawley, Jonathan, Willcocks, Chris G., Habib, Maged, Geenen, Caspar, Steel, David H. & Obara, Boguslaw (2021), Robust 3D U-Net Segmentation of Macular Holes, in Pakrashi, Arjun, Rushe, Ellen, Bazargani, Mehran Hossein Zadeh & Mac Namee, Brian eds, CEUR Workshop Proceedings 3105: The 29th Irish Conference on Artificial Intelligence and Cognitive Science 2021, Dublin, Republic of Ireland, December 9-10, 2021. Dublin, CEUR-WS.org, 36-47.
• 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, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Montreal, BC, Computer Vision Foundation / IEEE.
• 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.
• 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.
• 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.
• Bond-Taylor, Sam & Willcocks, Chris G. (2021), Gradient Origin Networks, International Conference on Learning Representations. Vienna / Virtual.
• Frawley, Jonathan, Willcocks, Chris G., Habib, Maged, Geenen, Caspar, Steel, David H.W. & Obara, Boguslaw (2020), Segmentation of macular edema datasets with small residual 3D U-Net architectures, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE). Cincinnati, OH, IEEE.
• 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.
• 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.

Doctoral Thesis

• Chris G. Willcocks (2013). Sparse Volumetric Deformation - Animating and rendering huge amounts of volumetric data using GPGPU computing. Durham University. PhD.

Journal Article

• Duan, Haoran, Long, Yang, Wang, Shidong, Zhang, Haofeng, Willcocks, Chris G. & Shao, Ling (2023). Dynamic Unary Convolution in Transformers. IEEE Transactions on Pattern Analysis and Machine Intelligence
• Bond-Taylor, Sam, Leach, Adam, Long, Yang & Willcocks, Chris G. (2022). Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 44(11): 7327 - 7347.
• 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.
• 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.
• 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.
• 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.