MSc Artificial Intelligence — First Class Honours
I build AI and data systems that help people inspect complex information, understand uncertainty, and make better decisions.
My work combines decision-support systems, machine learning, computational research, analytics, visualization, and technical education, with a particular interest in explainability and human judgement.
| Project | Focus |
|---|---|
| Explainable airline passenger-rights assistant | |
| 📊 BeLedgerReady | Financial anomaly analysis and audit-readiness assistant |
| 🚀 Industry-Integrated AI Systems Synthesis | Auditable AI decision-support architecture for aerospace safety |
| 🔥 PyroNav | Wildfire evacuation PWA with hazard-aware routing |
| ☀️ intibi | Interactive companion driven by H-alpha solar observations |
| 🐦 bioacoustic-topology | Computational exploration of birdsong manifold dynamics |
| 🧠 latent-physiological-topology | Exploratory physiological signal analysis |
| 🤖 design-of-agentic-workflows | Governed multi-agent workflow architectures |
I also build compact prototypes for hackathons, teaching, and exploratory research. These projects are deliberately scoped to test an idea, expose its limitations, and establish whether it deserves to grow.
Decision-support systems, LLM applications, agentic workflows, orchestration pipelines, explainable AI, machine learning, computer vision, and human-in-the-loop architectures.
Scientific exploration, anomaly analysis, signal and time-series analysis, computational experimentation, and research-oriented prototypes.
Exploratory analysis, dashboards, KPI design, data storytelling, business intelligence, and decision-support visualization.
AI and data mentoring, curriculum design, educational technology, technical writing, and project-based learning.
Languages & Development Python • SQL • Jupyter • Git • GitHub
AI & Machine Learning ML • Deep Learning • NLP • LLM Systems • Computer Vision
Data & Analytics Tableau • Power BI • EDA • Data Visualization • KPI Design
Research Scientific Computing • Signal Analysis • Anomaly Detection
Systems Agentic Workflows • Human-in-the-Loop AI • Decision Support
My systems perspective was strongly shaped by autonomous driving, where perception, localization, prediction, planning, and control must work together under uncertainty. My earlier projects in this field are collected in the Self-Driving Car Engineer portfolio.
Alongside technical work, I write about AI, language, cognition, representation, science, and the structural implications of emerging technologies.
- The Linguistic Creature: Language, AI, and the Survival of Information
- I Asked AI to Rate My Face. It Modeled My Mind Instead
- The World Is Not Made Of Things
- Spinors at the Intersection of Two Geometries
Education was my route into technology and remains part of my technical practice. I mentor learners, teach AI and data subjects, and design resources that help people move beyond reproducing procedures toward understanding systems, making decisions, and explaining their reasoning.
I entered technology from education, languages, and the humanities. A Google Developer Scholarship Challenge in 2017 led to sustained study across software development, deep learning, reinforcement learning, autonomous systems, data science, computer vision, and generative AI, culminating in an MSc in Artificial Intelligence with First Class Honours in 2026.
That path continues to shape how I build: with attention to evidence, clarity, explainability, uncertainty, and the people who must ultimately use a system.
Literature, language, music, and a persistent fascination with space influence the questions I explore, even when the result is a technical system.
