I'm a Computer Science graduate with a focus on Machine Learning, Computer Vision, and AI — currently completing my Honours with a research project on sequence modelling for clinical disease progression.
What drives my work:
- 🔬 Rigour — I care about leakage prevention, validation methodology, and reproducibility as much as the model itself
- 🛠️ End-to-end builds — from system architecture through to evaluation and writeup
- 🧩 Different domains — deep learning, NLP, multi-agent LLM systems, game dev, application dev
- 📚 Currently exploring State Space Models (Mamba) and Transformer architectures for healthcare
Python |
C++ |
C# |
Java |
JavaScript |
SQL |
HTML |
CSS |
PyTorch |
TensorFlow |
scikit-learn |
Hugging Face |
Pandas |
NumPy |
Unity |
SFML |
Shader Graph |
Git |
GitHub |
Linux |
VS Code |
Bash |
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Next-visit MMSE prediction using gated recurrent neural networks on the OASIS-2 longitudinal dataset. Highlights:
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A multi-agent system that autonomously generates, validates, and executes Python code. Highlights:
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Transformer-based résumé scoring system using BERT regression for consistent 0–100 quality scores. Highlights:
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3D third-person adventure platformer in Unity centred on a toy robot's journey to rebuild himself. Highlights:
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A C++ narrative-driven game with branching storylines and multiple endings driven by player decisions. Highlights:
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Comparative study of Mamba-based State Space Models vs Transformer architectures for disease progression modelling on longitudinal clinical data. Focus areas:
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- Computer vision & image processing — beyond classification, into spatial reasoning and segmentation
- State space models — Mamba, structured state evolution, linear-time sequence modelling
- Optimisation & modelling — mathematical techniques for structured decision problems
- Healthcare ML — longitudinal data, irregular sampling, time-to-event modelling
- Ontologies & knowledge representation — structured reasoning and knowledge bases
- Agentic AI — multi-model orchestration, tool use, persistent memory
