Dr. Gordon McDonald

Dr. Gordon McDonald

Informatics Team Lead

University of Sydney


Gordon McDonald is a Informatics Team Lead at the Sydney Informatics Hub, which is part of the University of Sydney. We consult in data science, visualisation and machine learning projects for academic researchers in all disciplines. Sometimes we work with external collaborators like government departments, hospitals and the police. Some days we’re automatically identifying australian native animals in camera traps, mapping fish behaviour in a tank 🐟, global mine waste 🌏 ⛏ or mercury levels, other days I’m automating high pressure liquid chromatography mass spectroscopy 💉 to detect metabolites more efficiently, and some time in between I’m looking at hospital patient data 🏥 to get them better outcomes.

I completed my PhD in Physics with the Atom Laser and Quantum Sensors group at the Australian National University. I used Bose-Einstein condensates to build new designs of sensors known as atom interferometers. These can be used to measure gravity (to find mineral and water 🌊 deposits, gravity waves 🌠), inertial accelerations (guidance systems 🛰, geology), magnetic 🧲 and electric fields ⚡️, and fundamental physical constants (fine structure, big G ⏱ ). One day they will be inside all sorts of technology in everyday life.


  • Data Science
  • Artificial Intelligence
  • Teaching
  • Physics


  • PhD in physics building quantum sensors, 2015

    Australian National University

  • Honours with university medal in physics, 2009

    Australian National University

  • Bachelor's in physics, chemistry and math, 2008

    Australian National University



Data Science Group Lead

Sydney Informatics Hub, University of Sydney

Jan 2019 – Present Sydney, Australia
Lead a team of Data Scientists and software engineers to provide technical knowledge and capability in data science to top-tier research at the university, often also involving external partner organisations.

Data Scientist

Sydney Informatics Hub, University of Sydney

Jan 2016 – Dec 2018 Sydney, Australia

Working as a data scientist at the Sydney Informatics Hub, I have been applying frequentist, machine learning and Bayesian statistical techniques to a variety of research projects to produce insightful answers from structured and unstructured data. Highlights include:


• An analysis of the relative risk of discharge against medical advice within the Sydney Children’s Hospital Network over five years of historical admissions records and 250k admissions, which I presented at the Health Data Analytics conference in Brisbane, October 2017.

• Clinical studies at the Woolcock Institute into sleep disorders such as insomnia and how they can be monitored with actigraphy measurements (i.e. a fitness wristwatch).

• Creating a software tool to streamline the process of analyzing metabolites through High Pressure Liquid Chromatography Mass Spectroscopy (HPLC-MS) at the Charles Perkins Centre.

• Developing a software tool to enable researchers to calculate chemical concentrations and kinetics in complex biological reactions involved in cell differentiation in developing spinal cords.


•Financial modelling for the NSW Department of Industry’s Smart and Skilled program for Vocational education and training, a program which allocates more than $600 million a year in subsidies for NSW students.

Social Science

• Correlating election results for the 2016 US presidential election and the 2016 UK Brexit election with demographics of each electoral region.

• Analysing crime data across NSW looking for spatiotemporal patterns which can be exploited to improve policing efficiency.

While partly taking on the role of university statistician (2018-19) I provided statistical assistance to researchers across the university including meta-analyses, survey analysis and statistical methods.

I have taught customized 2 to 5 day courses in statistical data analysis and machine learning both in R and Python, delivered at the University of Sydney, UTS, Macquarie University and Amazon.


Post-doctoral Researcher

Quantum Sensors and Atom Laser Group, Australian National University

Jan 2015 – Dec 2015 Canberra, Australia
I developed software to leverage principal component analysis, non-linear fitting and Fourier transforms to automate our image processing pipeline and extract relevant measurements for our physics research.

PhD Student

Quantum Sensors and Atom Laser Group, Australian National University

Jan 2010 – Dec 2015 Canberra, Australia
My PhD thesis is available here: Cold Atom Interferometry in Optical Potentials

Honours Student

Quantum Sensors and Atom Laser Group, Australian National University

Jan 2009 – Dec 2009 Canberra, Australia
My honours thesis is available here: Detecting Atomic Shot Noise On Ultra-cold Atom Clouds


Top 25 Analytics Leaders for 2020

I was recognised as one of the Top 25 Analytics Leaders for 2020 by the Institute for Analytics Professionals of Australia

Certified Software Carpentry Instructor

Certified as a qualified instructor to teach Software Carpetry lessons in R, Python and git

University Medal in Physics

University medal in physics for my thesis on detecting atomic shot noise in Bose-Einstein condensates.

Recent Posts

Some formulas to make working in Excel easier

Some excel formulas to make things that should be easy less impossible

Using ellipsis (...) and purrr::pmap()

How to write functions with arbitrary arguments and then map them over data frames.

Recent Publications

Quickly discover relevant content by filtering publications.

Stop motion: using high resolution spatiotemporal data to estimate and locate stationary and movement behaviour in an office workplace

Prolonged periods of stationary behaviour, a common occurrence in many office workplaces, are linked with a range of physical …

Health promotion interventions to improve oral health of adolescents: A systematic review and meta-analysis


To evaluate the effectiveness of health promotion interventions on oral health knowledge, behaviour and status of healthy …

Discharge against medical advice in culturally and linguistically diverse Australian children

Objectives This study quantifies the prevalence and rates of discharge against medical advice (DAMA) in culturally and linguistically …

Fine-scale behavioural adjustments of prey on a continuum of risk

In the wild, prey species often live in the vicinity of predators, rendering the ability to assess risk on a moment-to-moment basis …

Predictors of Discharge Against Medical Advice in a Tertiary Paediatric Hospital

Background: Patients who discharge against medical advice (DAMA) from hospital carry a significant risk of readmission and have …