I am developing deep learning models to improve the classification of mammograms and researching the integration of artificial intelligence (AI) into real-world breast screening programs. I use my skills and experience and my passion for data visualisation and software design to develop tools that can enhance scientific communication and translate technical understanding into actionable insights.

Following completion of my PhD in Statistics, I completed postdoctoral studies in Bayesian Econometrics at The University of Melbourne. In 2020, I was awarded two grants from the R Consortium, to develop an R-to-JavaScript transpiler that assists researchers in creating animated and interactive visualisations for high-quality and engaging science communication.

Key achievements

2020   R Consortium Grant (2 grants received, in Fall and Spring granting rounds)

2015   Outstanding Tutor Prize

2014-2018   Melbourne International Fee Remission Scholarship

2014-2017   Melbourne International Research Scholarship

2014   Kinsman Studentship; Kinsman Prize

2012   Institute of Actuaries Australia Honours Prize

2009-2010   University of California, Berkeley (USA); Education Abroad Program (Mathematics)

Bioinformatics & Cellular Genomics

We focus on the challenges of analysing and interpreting large-scale biological data. Bringing together expertise in bioinformatics, statistics and machine learning, we develop new methods and software and collaborate closely with a wide range of colleagues on studies motivated by specific biologically-focused questions.

Lab head: Associate Professor Davis McCarthy

View lab profile

Selected publications

Helen ML Frazer, Carlos A Peña-Solorzano, Chun Fung Kwok, Michael Elliott, Yuanhong Chen, Chong Wang, the BRAIx team, Jocelyn Lippey, John Hopper, Peter Brotchie, Gustavo Carneiro, Davis J McCarthy. AI integration improves breast cancer screening in a real-world, retrospective cohort study. medRxiv preprint server for health sciences. doi.org/10.1101/2022.11.23.22282646

Helen ML Frazer, Jennifer SN Tang, Michael S Elliott, Katrina M Kunicki, Brendan Hill, Ravishankar Karthik, Chun Fung Kwok, Carlos A. Peña-Solorzano, Yuanhong Chen, Chong Wang, Osamah Al-Qershi, Samantha K. Fox, Shuai Li, Enes Makalic, Tuong L. Nguyen, Daniel Schmidt, Prabhathi Basnayake Ralalage, Jocelyn F Lippey, Peter Brotchie, John L Hopper, Gustavo Carneiro, Davis J McCarthy. ADMANI – annotated digital mammograms and associated non-image datasets. Radiology: Artificial Intelligence (in press)

Chun Fung Kwok (2022). sketch: Interactive Sketches. R package version. 1.1.19. https://CRAN.R-project.org/package=sketch

ORCID profile: 0000-0002-0716-3879