I'm a Master of Data Analytics student at Queensland University of Technology with a passion for building machine learning systems that solve real problems. My work spans predictive modelling, deep learning for medical imaging, and end-to-end data pipelines — from raw data to interpretable, deployable insights. Currently broadening my toolkit into AI engineering and LLM applications.
Who I Am
Building models that extract meaningful insight from complex, real-world datasets.
From raw data wrangling to statistical modelling — fluent across the full analytics stack.
I enjoy breaking hard problems into elegant, testable solutions — one hypothesis at a time.
Tech Stack
What I've Built
Deep learning framework that classifies COVID-19 from chest radiographs using transfer learning. Evaluated 14 pre-trained CNN architectures (DenseNet, ResNet, VGG, MobileNet, Inception-v3 and more) on 6,669 images. Best models (DenseNet-121, DenseNet-161, ResNet18) achieved >90% sensitivity and >94% specificity.
LightGBM model trained on 1.2M ICU admissions (177 variables) from the ANZICS Adult Patient Database, benchmarked against the published ANZROD20 score (AUROC 0.918). Used patient-grouped StratifiedGroupKFold cross-validation to prevent leakage, Optuna for hyperparameter tuning, and SHAP for interpretability. Evaluation spans discrimination, calibration, decision curve analysis, and demographic fairness audits.
Background
Queensland University of Technology (QUT), Brisbane, Australia
2023 – 2025
Postgraduate studies covering advanced data analytics, machine learning, statistical modelling, and data-driven decision making.
Get In Touch
I'm open to internships, graduate roles, research collaborations, or simply a good conversation about data. Reach out — I'd love to hear from you.