I'm an IT graduate from Adelaide University, majoring in Artificial Intelligence and Machine Learning, and most days you'll find me somewhere between a dataset, a broken system, and a cup of coffee, trying to make sense of all three. My work stretches across data analytics, IT support, and software engineering, and I like it that way. Data analytics gives me the puzzle, IT support gives me the fix, and software engineering gives me something to build once I've figured both out.
I keep my problem solving sharp on LeetCode, work in Python, SQL, Power BI, and Java, and spent time as a research assistant at university, which taught me just as much about asking the right question as finding the answer.
Outside of the technical work, I'm an active member of the ACS and served as COO of Women in Leadership Management, where I got to spend time on something I care about just as much as code: making sure more people feel like they belong in tech and in leadership.
A quick overview — each project below shows the specific tools used for that piece of work.
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Trained a model to predict neural state changes from EEG data, achieving 81% accuracy.
Data-driven Power BI dashboard highlighting key customer personas and retention strategies.
Built a Random Forest model to predict at-risk customers and inform retention strategy.
Interactive Excel dashboard summarising sales performance, product trends, and regional hits.
Forecasted hourly bike rental demand in Seoul using regression models, cutting prediction error well below a mean-baseline model.
Built a 1-Nearest-Neighbor classifier from scratch using a k-d tree, optimizing nearest-neighbor search over brute-force comparison.
Built a classifier to detect malignant tumours from histological cell measurements, benchmarked against clinical baselines.
Verified credentials and clearances.