Portfolio

Below are a few of my recent Research, Collaborations, Publications and then finally Portfolio. Some client projects are linked under the Portfolio Nav menu and some videos are on YT. If you have any requests, issues, comments, improvements or would like to view/download My Portfolio, please feel free to drop an me email or DM.

ReSEARCH & Development

‘Build a Lightstage’ Project (2015-).

Keywords: Photometric Stereo; Physics Simulation; Geometry; Numerical Optimisation; OpenGL Visualisations; Agri-tech; 3d Reconstruction; Feeding the Future; Morphological Identification; Climate Change Resilience in Crops.

This is my first post-doctoral research project at Aberystwyth University with funding from University’s Research Fund grant (URF) and supported by National Plant Phenomics Centre, UK. Principal Investigator is Dr. Hannah Dee. The project involved the following:

  • Open Source 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. (Dedicated website details here).
  • Building the Spherical Lightstage Structure and triggered image capture platform, see details on Dr. Dee’s post.


‘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; Manufacturing; Critical National Infrastructure.

This was my Doctoral (PhD) research project 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 Pipelines 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.

This is an early proof-of-concept demo video of CARDINAL-E (2013) – one of the variants of the distributed self-healing system algorithm. In the video the software 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 include:

  • 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 robotic 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…

Publications:

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

portfolio:

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

If you are interested in my work or you’d like to Download My Portfolio (10 pages, full of techie stuff), then please ping me an email or a DM with your name and request and I will reply within 24 hrs.

Recent Posts

TIL: Fixing ‘file not found’ dependency libraries in Linux

In Ubuntu (Debian/CentOS, and the like) apt is our go to CLI application package installer. It handles everything in a single iconic command that every Linux user knows: sudo apt install <packageName> Sometimes, and I still don’t get why or when, a package’s shared library (dependency) is not installed. For example, this happened today for … Continue reading TIL: Fixing ‘file not found’ dependency libraries in Linux

On Measuring the Senior, In Senior Software Engineering Roles

Labelling “Senior”, “Mid” and “Junior” roles of software engineers comes up from time to time in the developer and programmer forums. While I’m not a fan of labels for people or groups of people – Seniority and Skill/Knowledge/Ability Levels get to me because they are so ambiguous. So it is down to us to contribute and discuss to reach a clear definition.

A truth of seniority, across all genres, is group-wide effect. It’s leadership, it’s empathy, it’s improving the individuals and the group as a whole for the group’s common interest. It’s a positive improvement. But what does that mean for Developers and Software Engineers?

Adding to the Conversation on Data Science Training: Looking into the Future

Conversation on Data Science Training: Looking into the Future — While I have been hesitant to define the structure of data science training, and I am biased towards (as I have) a Comp Sci background. I conversely follow the doctrine that “comp sci is without purpose with no application”, owing to my position of “domain knowledge is where the value is generated” (societal, financial, etc). If setting boundaries and principles in Data Science is required, I think it’s the view of the future that must be settled first….

Book review 2/2 on Robot Proof: Higher Education in the Age of AI

I finished the book by Joseph Aoun a little while ago, and I’ve been sitting on my notes letting them stir. I think i have a fairly safe conclusion for its second half. That said, I would expect those with an understanding and empathetic relationship with their CS students and their families will have been … Continue reading Book review 2/2 on Robot Proof: Higher Education in the Age of AI

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