My interdisciplinary research focuses on providing elegant solutions to computationally expensive or ill-defined problems within the fields of machine learning, high-performance computing, image processing, bioimage informatics and computer graphics.


  • Extracting 3D Parametric Curves from 2D Images of Helical Objects,
    Chris G. Willcocks, Philip T.G. Jackson, Carl J. Nelson, Boguslaw Obara,
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PP, No. 99, p.1–1 2016.
  • Interactive GPU Active Contours for Segmenting Inhomogeneous Objects,
    Chris G. Willcocks, Philip T.G. Jackson, Carl J. Nelson, Amar Nasrulloh, Boguslaw Obara,
    In Review: Journal of Real-time Image Processing, 1 2017.
  • Quantized Temporal Visualization of Deep Convolutional Neural Networks,
    Chris G. Willcocks, Samet Akcay, Philip T.G. Jackson, Boguslaw Obara,
    In Review: International Journal of Computer Vision 2017.
  • Multi-scale Segmentation and Surface Fitting for Measuring 3D Macular Holes
    Amar V. Nasrulloh, Chris G. Willcocks, Philip T.G. Jackson, C. Geenen, M. Habib, D. Steel, Boguslaw Obara,
    Submitted: IEEE Transactions on Medical Imaging, 7 2017.
  • On Using Deep Convolutional Neural Network Architectures for Automated Object Detection and Classification within X-ray Baggage Security Imagery
    Samet Ackay, Mikolaj Kundegorski, Chris G. Willcocks, Toby P. Breckon,
    Submitted: Pattern Recognition, 6 2017.
  • Sequential Graph-based Extraction of Prominent Curvilinear Structures
    S. Alharbi, Chris G. Willcocks, Philip T.G. Jackson, Boguslaw Obara
    In Review: IEEE Transactions on Pattern Analysis and Machine Intelligence, 8 2017.
  • The Relationship between Enhancement and Skeletonization in Biological Networks,
    Haifa Alhasson, Chris G. Willcocks, Philip T.G. Jackson, Boguslaw Obara,
    In Prep: Medical Imaging Analysis 2017.
  • Subtle Attention with Wasserstein Generative Adversiaral Networks,
    Chris G. Willcocks, Boguslaw Obara,
    In Prep: Foundations and Trends in Machine Learning 2018.
  • Pyproc: a Python Library for Generating Synthetic Training Data for Deep Learning Applications,
    Chris G. Willcocks, Philip T.G. Jackson, Boguslaw Obara,
    In Prep: Foundations and Trends in Machine Learning 2017.
  • Automatic 3D Segmentation for Measuring Intraretinal Cysts,
    Amar V. Nasrulloh, Chris G. Willcocks, Philip T.G. Jackson, Boguslaw Obara,
    In Prep: IEEE Transactions on Image Processing 2018.
  • Feature-varying skeletonization: Intuitive control over the target feature size and output skeleton topology,
    Chris G. Willcocks, Li, Frederick W. B.,
    The Visual Computer, International Journal of Computer Graphics, CGI, Vol. 28, No. 6, p.775–785 2012.

Conferences and Workshops

  1. Application of high-speed level set segmentation to light sheet fluorescence microscopy,
    Carl J. Nelson, Chris G. Willcocks, Philip T.G. Jackson, Philippe Laissue, Boguslaw Obara,
    Light Sheet Fluorescence Microscopy International Conference, 8 2016.
  2. Real-time segmentation of brain vasculature and identification of anomalies in magnetic resonance angiography,
    Nitin Mukerji, Carl J. Nelson, Chris G. Willcocks, Philip T.G. Jackson, Boguslaw Obara,
    European Congress of Neurosurgery, 9 2016.


  1. Sparse Volumetric Deformation, Animating and rendering huge amounts of volumetric data using GPGPU computing,
    Chris G. Willcocks,
    PhD thesis, Durham University, 10 2013.

Research Interests

  • Unsupervised Learning
  • Level Set Methods
  • Big Data Analytics
  • Image Processing
  • GPGPU Computing
  • Deep Learning
  • Data Visualization
  • Segmentation & Skeletonization
  • Optimization
  • HPC Computing