Resume

Designed and delivered optimized data mining algorithms that:

• assemble complex SQL queries and use NLP and other techniques in Python to analyse and recover features from a large volume of unstructured data,
• achieve average parsing times of less than 1 millisecond per entity profile over 97% of data without external API calls,
• score the degrees of similarity between entity profiles using Python and upload scores to BigQuery.

Wrote documentation, status reports and updates, and gave regular non-technical presentations to stakeholders.

• Modelled and simulated disease transmission dynamics,
• Evaluated and analysed the effectiveness of interventions,
• Investigated behavioural and social responses to vaccination campaigns.

Co-developed software with ApexRMS to use their SyncroSim application to compare and chain together COVID-19 models written in R, Python and C#.

Proposed new techniques useful for quantitative analysis and prediction of epidemics and public health crises in a computational model pairing an infectious respiratory disease with social media dynamics using:

• continuous testing algorithms,
• time series analysis,
• machine learning (NLP, regression, cluster analysis, etc),
• extensive statistical and data analysis.

This work resulted in three published articles. See project work

Computational Epidemiology

My research focused on finding Early Warning Signal (EWS) metrics that can be used to predict epidemics of a measles-like vaccine preventable infectious disease spreading through a large population where the majority of individuals are susceptible to infection.
See project work

Courses taken in

• Topology
• Graph Theory
• Algebra
• Mathematical Biology

Courses taken in

• Pure Mathematics
• Applied Mathematics
• Econometrics
• Statistical Analysis
• Philosophy of Science