Development | R&D Projects

‘Building a Lightstage’ Project (2015-).

Keywords: Photometric Stereo; Physics Simulation; Geometry; Numerical Optimisation; OpenGL Visualisations; Agri-tech; 3d Reconstruction.

Post-doctoral research project on Building a Lightstage at Aberystwyth University with funding from University’s Research Fund grant (URF) and supported by National Plant Phenomics Centre, UK. Principal Investigator Dr. Hannah Dee.

  • Open Source software development of experimental framework, for numerical optimisation using Computer Vision techniques and exporting results to the platform.
  • Designing numerical physics methodology to evaluate light and camera positioning for data capture, using less and improved data, for Photometric Stereo, Structure-from-Motion and 3d Reconstruction pipelines.
  • Building of the spherical Lightstage structure and triggered image capture platform.

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‘Self-Healing Architectures Against Malware’ PhD Project (2011-15)

Keywords: Self-Healing Systems; Cyber Security; Artificial Immune Systems; Distributed; Computer Network; Peer-to-Peer; Decentralised; Industrial Control Systems; Robotics;

Doctoral research at Aberystwyth University funded by EPSRC and Airbus Group Innovations and advised by Dr. Mark J. Neal, David E. Price and Dr. Jules Pagna Disso.

  • Researched Self-Healing Systems from Cyber Attacks on Critical Infrastructure and Manufacturing Automation devices, such as Industrial Control Systems and SCADA networks. The PhD thesis experimentation focused on an intelligent Artificial Immune System framework called CARDINAL.
  • Designed Machine Learning Pipeline for Network Security datasets, including phases: feature selection, self-supervised Fuzzy-clustering, supervised C4.5 decision tree. Co-authored results in Cyberspace Safety and Security 2013 proceedings paper and Journal of Computers 2014 article.
  • Reformatted, maintained and host the CSIC 2010 HTTP Dataset in CSV Format for training Machine Learning models applied to web application security, a subcategory of Network Security problems.

An early proof-of-concept demo video of CARDINAL-E (2013) – showing a demo of the distributed self-healing system algorithm. It is parsing network packet inputs via the tshark parser (Wireshark), selecting and learning from high discrepancy features selected from KDDCup’99 dataset and sharing learnt signature profiles between the two instances on virtual machines and connected via the local loopback device.

Other COLLABORATION R&D Projects included:

  • Cyber Security Robotic Testbed for SCADA Networks — Design, procure, build, write & test code for a programmable logic controller (PLC) attack testbed. Network dataset collection for Stuxnet/Flame style attacks. The hardware used was Siemens S7-312 series PLC with CP343-1 networking module, distributed communication processor CP343-2P over an actuator sensor interface (AS-I) bus to operate a grabber and arm with seven degrees of freedom.
  • Cyber Security Dataset — Hosted, maintained & supported reformatted revisions of the CSIC 2010 HTTP web penetration and network attack dataset for the network security machine learning community.
  • Data Mining Publications on Network Security Datasets — Design, write & test the C4.5 decision tree with a modified mutual information feature selection (MMIFS) algorithm resulting in improved performance on KDDCup datasets. Collaboration with Dr. Jingping Song.
  • Data Mining on Biological Pathway Investigations — Combined >500 curated biomodels (from EBI) using SBML libraries with chemical protein interaction datasets (from STITCH) to explore chemical pathway patterns within the biological models.
  • plus various others…


For more publications and research activity, see Google Scholar, DBLP, ResearchGate or

Portfolio of Projects:

For a portfolio of software (and in cases, hardware) development projects including the operational roles and the development stacks used, please see the Portfolio of Workflows and Stacks page.

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