Johanna Bayer has a formal background in psychology and computational neuroscience, and is completing her PhD in machine learning for clinical neuroimaging at the University of Melbourne in Australia. Her research brings machine learning methods to brain imaging data, work that sits at the intersection of clinical neuroscience, statistics, and large-scale data analysis.

At the University of Melbourne, Johanna discovered the field of research software engineering, and it has become a defining part of her work. She teaches and promotes the practices that make research code trustworthy, from version control and testing to packaging, environments, and reproducible manuscripts, so that scientific results can be verified and reused rather than lost. She has contributed to several open-source projects along the way.

Johanna is a vocal advocate for open source and open science, arguing that research software deserves the same care and recognition as papers. She also supports the wider data community, preparing interview questions for guests on the DataTalksClub podcast and helping researchers adopt better coding practices through workshops and community teaching.