Software Engineer – This site is under construction
Portfolio
About me
I am a final year student completing a double degree at the University of Canterbury. Towards a degree in Software Engineering I have focused on Machine Learning, Computer Graphics and Model Driven Software Engineering. Examples of projects completed can be found above.
I am now finishing off a Bachelor of Science majoring in Mathematics and Philosophy, graduating at the end of 2020.
My professional experience includes development of a remote monitoring system for an agricultural equipment manufacturer, and for a GIS software company I worked as an intern fixing bugs and developing features.
I am also a keen musician, playing for local bands and orchestras.
Contact Me
Machine Learning
I have taken courses in Artificial Intelligence and Machine Learning, covering a variety of topics including:
The A* search algorithm,
Declarative programming in Prolog,
Decision trees,
Neural networks and Deep Learning,
Reinforcement and Ensemble Learning,
Learning theory and Information theory.
The majority of my experience involved programming in Python. In particular, my honours project was aimed at extending the decision trees module of Scikit-learn, the popular machine learning library for Python.
Experience includes using OpenGL 4 to render a terrain map with height-based texturing as well as character animation together with the Blinn-Phong lighting model. The projects were developed in C++.
I also have experience with simple ray-tracing concepts.
I have experience creating a JavaScript web app which uses a Node backend and Vue.js for the frontend.
This site is powered by WordPress with a custom theme derived from the Freelancer theme for Bootstrap. It is hosted by Amazon Web Services.
I was also involved in a year-long university group project developing an "organ donation management system" with a desktop and mobile client. The app was developed using the cross-platform framework Xamarin to support both iOS and Android devices.
I developed a system to analyses the movements of a conductor in order to identify where the beats of a musical performance occurred.
The system was developed in Python using the OpenCV library. It combines simple techinques with a pre-trained neural net to track the hands of a composer.
