The Computational Science Centre for Research Communities (CoSeC) enables and supports collaborative computational research communities that are funded across UKRI. It has a mission to deliver research software as an infrastructure to enable world-class UK Research and Innovation.
The CoSeC Impact Award recognises individuals whose work has significant impact (REF definition of impact) for computational research, in close collaboration with CoSeC and related communities.
X-ray Computed Tomography (XCT) creates non-destructive 3D images for medical diagnosis and manufacturing defect detection, but dense or multi-material objects often suffer from "beam hardening," a distortion that blurs details and can introduce false features. Sunny's doctoral research tackles this with the Beam Hardening Predictive Index (BHPI), which predicts beam hardening severity before scanning, and a closed-loop pipeline—built with Collaborative Computational Project in Tomographic Imaging (CCPi)'s gVirtualXray (gVXR simulator and the Core Imaging Library (CIL) reconstruction tools—that tests thousands of voltage and filter combinations to optimise scan settings.
Sunny Nwokolo says, “I am honoured to receive the 2026 CoSeC Impact Award. The Beam Hardening Predictive Index (BHPI) grew from a simple question: can we predict and plan around beam hardening before a scan is taken, rather than correcting for it afterwards? Getting there depended entirely on the open tools and the community behind them, gVirtualXRay and the Core Imaging Library (CIL), and on the support of CCPi and CoSeC. I am grateful to my supervisor, Franck Vidal, STFC Scientific Computing to Jean Michel Létang, INSA Lyon - Institut National des Sciences Appliquées de Lyon, and to all my collaborators, and I hope BHPI proves genuinely useful across the many fields that rely on X-ray CT.”
Sunny will talk about his research at IBSim & #gVXR User Meeting at the Institute of Physics in October.
Read Sunny Nwokolo's latest paper "A beam-hardening predictive index (BHPI) for simulation-guided spectral optimisation in laboratory X-ray.
