I have a Ph.D. in Plant Biochemistry. I have a decade of Post-doc experience as:

• Research fellow in Professor Ruediger Hell’s laboratory at the University of Heidelberg (2010-2012)
• EMBO long term fellow in Professor Lee Sweetlove’s laboratory at the University of Oxford (2012-2014)
• Research associate in Professor Harvey Millar’s laboratory at the University of Western Australia (2014-2021)

The main theme of my previous research projects was "Plant mitochondrial membrane carriers". I was responsible for collecting small to medium scale data (3-100 samples) of at least two variables (i.e. genotypes and/or conditions), analysing data with appropriate statistics, teaching and mentoring/leading students.

Check out my previous Publications!

I am currently working in the public sector as a data analyst.

This is a R-based web scraping app for obtaining gene annotation and transmembrane domain information of a large number of genes from ARAMEMNON. This is entirely a web-based app, so you don't have to worry about reading, writing or modifying codes - just run the script in R, upload your gene list, grap your coffee/tea and wait for the job to finish. The script feeds your list of plant genes into the database and returns a table for determining whether your genes are soluble/peripheral or membrane proteins and the number of predicted transmembrane domains according to the Consensus TM alpha helix prediction (AramTmCon). The app was built using RStudio.

Repository under construction

A R script I routinely used for reporting data exported from the Agilent MassHunter Quantitative Analysis Software in an instance. This script will transform multi-index excel table into appropriate dataframe and normalise raw data using a user-entered normalisation factor(s). Multiple bar graphs will then be generated (depending on the number of experimental conditions/variables) in one panel and statistical analysis is carried out using one-way ANOVA, normality tests and post-hoc Tukey test. The fully automated process takes only a few seconds to go through hundreds of samples.

In this project, I analyzed the public sector employee perception survey data conducted by the Western Australia Public Sector Commission in 2015, available here. Using the data, I examined if there are gender gaps in job satisfaction, salary and career opportunities within the WA public sector. Access the analysis by clicking here (Jupyter Notebook report) or by clicking here (Power BI dashboard). The report was generated using Jupyter Notebook with SQL and Python as the languages for data cleaning, manipulation and visualisation.

A Power BI Dashboard showing the locations and types of public toilets in Australia. Data source: data.gov.au