Dr Saskia Bollmann

Research Fellow

School of Electrical Engineering and Computer Science
Faculty of Engineering, Architecture and Information Technology


I obtained my M.Sc. ETH in Biomedical Engineering from the Swiss Federal Institute of Technology Zurich in 2013, where I utilized concurrent magnetic field monitoring to improve image quality and temporal stability of functional magnetic resonance imaging (fMRI). I then moved to Brisbane in 2014, to pursue a PhD at the Centre for Advanced Imaging, The University of Queensland under the supervision of Prof. Markus Barth. I investigated contrast mechanisms and signal properties of fMRI focusing on ultra-high field applications. In 2019, I joined A/Prof. Jonathan Polimeni at the Martinos Center for Biomedical Engineering, Massachusetts General Hospital, where I employed ultra-high field MRI to image the blood vessels of the human brain, and better understand their contribution to the fMRI signal. I returned to Brisbane in 2020 as acting 7T NIF Facility Fellow at the Centre for Advanced Imaging and I am currently a Research Fellow at the School of Information Technology and Electrical Engineering, Faculty of Engineering, Architecture and Information Technology. I am devloping new contrast mechanisms for funtional MRI and I am investigating the effect of the vasculature on the fMRI signal.


  • Doctor of Philosophy, The University of Queensland


  • Chen, Jingyuan E., Polimeni, Jonathan R., Bollmann, Saskia and Glover, Gary H. (2019). On the analysis of rapidly sampled fMRI data. NeuroImage, 188, 807-820. doi: 10.1016/j.neuroimage.2019.02.008

  • Bollmann, Saskia, Puckett, Alexander M., Cunnington, Ross and Barth, Markus (2017). Serial correlations in single-subject fMRI with sub-second TR. NeuroImage, 166, 152-166. doi: 10.1016/j.neuroimage.2017.10.043

  • Bollmann, Saskia, Kasper, Lars, Vannesjo, S. Johanna, Diaconescu, Andreea O., Dietrich, Benjamin E., Gross, Simon, Stephan, Klaas E. and Pruessmann, Klaas P. (2017). Analysis and correction of field fluctuations in fMRI data using field monitoring. Neuroimage, 154, 92-105. doi: 10.1016/j.neuroimage.2017.01.014

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PhD and MPhil Supervision

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