Dr Kirstie Whitaker

Kirstie Whitaker

Position

Programme Director for Tools, Practices and Systems

Partner Institution

Bio

Kirstie discovered the wonder of brain imaging at the University of British Columbia during a masters degree in Medical Physics. She completed a PhD in Neuroscience at the University of California, Berkeley in 2012 and joined the Turing Institute as a Turing Research Fellow in 2017 from a postdoctoral fellowship at the University of Cambridge in the Department of Psychiatry.

In 2020, she was promoted to Programme Lead for Tools, Practices and Systems, and in 2021 to Programme Director, reflecting the growth of this cross cutting programme. Kirstie is committed to realising the TPS community's mission of investing in the people who sustain the open infrastructure ecosystem for data science.

Kirstie is the lead developer of The Turing Way, an openly developed educational resource inspire, train and enable researchers and citizen scientists across government, industry, academia and third sector organisations to apply open source practices to their work. She is also the chair of the Turing Institute's Ethics Advisory Group.

Kirstie is a passionate advocate for making science "open for all" by promoting equity and inclusion for people from diverse backgrounds, and by changing the academic incentive structure to reward collaborative working. She is a Fulbright scholarship alumna and was a 2016/17 Mozilla Fellow for Science.

Kirstie was named, with her collaborator Petra Vertes, as a 2016 Global Thinker by Foreign Policy magazine.

You can follow her and her dog's adventures on Twitter @kirstie_j.

Research interests

Adolescence is a period of human brain growth and high incidence of mental health disorders. Kirstie's research uses magnetic resonance images to understand changes in the brain's structure and function that underlie the emergence of schizophrenia and depression. Her work considers the brain as a network and investigates how different brain regions work together. She is particularly passionate about ensuring that work is reproducible and can be replicated in independent data sets. Her focus at the Turing Institute is to improve the generalisability of research findings so they may be translated to the clinic and used by public health policy makers.