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Dilan Pathirana


location_icon   Endenicher Allee 64, 53115 Bonn, Germany

phone_icon   +49 (0) 228 73 62264

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Short CV

Dilan studied molecular biology and applied mathematics at Griffith University (Australia), with an honours year in experimental molecular biology. He then completed a PhD at the same university, which involved the mathematical modelling of aspects of the congenital heart disease Coarctation of the Aorta in arterial blood flow models, to identify possible causes of, and solutions to, patient issues.

Dilan initially joined the Hasenauer group as a Lift-Off Fellow, to study the behavior of subpopulations of natural killer cells, and is now continuing this work as a postdoc in the group.


  • Wayne A Schroder, Thiago D Hirata, Thuy T Le, Joy Gardner, Glen M Boyle, Jonathon Ellis, Eri Nakayama, Dilan Pathirana , Helder I Nakaya, and Andreas Suhrbier (2019). SerpinB2 inhibits migration and promotes a resolution phase signature in large peritoneal macrophages. Scientific Reports, 9 (1): 1--15.
  • Dilan Pathirana , Barbara Johnston, and Peter Johnston. (2019) The effect of including increased arterial stiffness in the upper body when modeling Coarctation of the Aorta. Computer Methods in Biomechanics and Biomedical Engineering, 22 (5): 475--489.
  • Dilan Pathirana, Barbara Johnston, and Peter Johnston (2017). Predicting the Effects of Straight and Tapered Stents on Blood Flow Properties in the Aorta. In CMBE 2017 Proceedings, 2:1224--1227. CMBE Zeta Computational Resources Ltd.
  • Dilan Pathirana, Barbara Johnston, and Peter Johnston (2017). The effects of tapering and artery wall stiffness on treatments for Coarctation of the Aorta. Computer Methods in Biomechanics and Biomedical Engineering, 20(14):1512--1524.
  • Dilan Pathirana, Barbara Johnston, and Peter Johnston (2016). Predicting blood pressure in aortas treated for coarctation. ANZIAM Journal, 57:32--50.


  • Modelling subpopulations of natural killer cells
  • Development of modelling tools, including simulation (AMICI), and model selection (pyPESTO)                          
  • GlukoSys : insulin regulation for patients in intensive care
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