MSc Data Science and Artificial Intelligence at Queen Mary University of London (graduating September 2026, on track for distinction). Building end-to-end experience across machine learning, statistical modelling, and applied AI.
Actively seeking graduate and entry-level roles in data science, machine learning engineering, and AI research, available from September 2026.
Languages: Python · SQL
Data & Analysis: Pandas · NumPy · SciPy · Statsmodels
Machine Learning: Scikit-learn · XGBoost · LightGBM · CatBoost
Deep Learning: TensorFlow · PyTorch · Hugging Face Transformers
Visualisation: Matplotlib · Seaborn · Plotly
Tools: Git · Jupyter · Google Colab
| Project | Summary | Stack |
|---|---|---|
| Speaker-Independent Song Classification | Audio ML pipeline classifying hummed and whistled recordings across 8 song classes, with participant-disjoint evaluation to test generalisation to unseen users | Python · Scikit-learn · Librosa |
| UK Climate Trend Analysis | Statistical modelling of long-run Met Office data across 37 stations to quantify warming trends, regional variation, and frost-occurrence change | Python · SciPy · Statsmodels |
| Bridge Condition Modelling | Regression and exploratory analytics on 33,000+ Texas bridges to identify the structural and operational factors most associated with condition | Python · Scikit-learn · Pandas |
| COVID-19 IR Search Engine | Biomedical information retrieval pipeline for COVID-19 literature, covering indexing, query processing, and ranked retrieval | Python · NLP |
| Large-Scale Text Processing | Memory-aware corpus analysis, Jaccard similarity, and inverted indexing in core Python | Python |