My Story

I started in computing in the early 1980s when command line and character based terminals ruled the IT world. I graduated from university with a BSc in computing science in 1985 (fun fact - the first semester we primarily used punched card!). Since graduating I've worked at the technical side of the industry from research, to defence projects, software tools to business systems. Throughout, I managed to keep my skills current and wangled a seat at the forefront of many innovations to the industry. This included being one of the very first adopters of Java, worked on internet applications when the only web browser we needed to support was Mosaic and Netscape Navigator. I was involved in agile programming methods before the term existed, via the Boehm Spiral Model. I first came across object oriented programming when objects were called Frames and Smalltalk was the main OO programming language. What did pass me by at the time was Python - well, you can't win them all (I'm fully Pythonesque now).

The first role I had when I entered the job market was with a research institude called the Marconi Researh Centre. I was part of the software engineering and AI team (yes - AI was a thing, even back then). I worked on various knowledge-based frameworks (AKA expert systems), but was never comfortable that I really knew what I was doing. As I moved towards the twighlight of my career, and having taken a sabbatical from the IT coal-face, it felt like a nice way to bookend my career would be to go back to college and learn what AI is really all about. An MSc programme at York University followed in computer science with AI. I graduated with distinction in the summer of 2023. The title of my dissertation was "The identification of garbage dumps in Cyprus through the application of convolutional neural networks to satellite imagery".

Whilst working on my dissertation I came up with the idea of developing an application that abstracts out the technical aspects of machine learning/image recognition, to produce something I think of as "AI land classification made simple(ish!)". Out of this was born deepTerra.

The application has grown organically from the requirements for my reseaches, so it is based on performing actual work in the area of land classification and features tools that simplify the process of collecting, augmenting, training and prediction.

I am planning to begin studying for a doctorate in the fall of 2024. When not playing around with machine learning, I like to climb rocks and fight pterodactyls, sometimes at the same time. I have a rare bone marrow disorder called myelodysplasia.