Background
I trained as a research scientist in respiratory immunology (PhD, UniMelb). During my post-doctoral research, I learnt R programming and applied statistical and machine learning workflows to discover how the human body orchestrates complex defensive processes against respiratory virus invasion.
I now work (and greatly enjoy working) in the public sector as a data scientist.
Education
- Ongoing: Graduate Certificate of Actuarial Statistics - Australian National University
- 2009-2014: PhD - University of Melbourne
- 2008: Bachelor of Science (Honours) - University of Melbourne
- 2005-2007: Bachelor of Biomedical Science - University of Melbourne
Interests
- Machine learning explanability
- Machine learning ethical frameworks
- Open government data initiatives
- Improving data science career pathway accessibility
Public projects
Introduction to Python workshop materials
A repository of beginner-friendly Python tutorials compiled from the Research Platform Services Python workshops (UniMelb, 2019) and the DIPA Introduction to Python workshop (Data61, 2020). Each tutorial exists as a self-contained Jupyter notebook and some tutorials make use of public data sources.Introductory mathematics in R and Python
A repository of introductory mathematics notes for beginners who are keen to understand how machine learning algorithms work but find the mathematical notations and concepts confusing (don’t worry - they really are just confusing).