Dr Thiranja Prasad Babarenda Gamage

BE(Hons) PhD Auck.

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Research Fellow


Thiranja Prasad Babarenda Gamage is a Research Fellow at the Auckland Bioengineering Institute (ABI). In 2016, Prasad completed his University of Auckland PhD on techniques for analysing constitutive parameter identifiability and the design of experiments for applications in breast biomechanics. His research focuses on developing data-centric engineering technologies and infrastructure for the clinical translation of computational models. Prasad co-leads the ABI’s Breast Biomechanics Research Group, who work on implementing these techniques in collaboration with clinical colleagues. This work is supported by the Breast Cancer Foundation of NZ and the University of Auckland Foundation. Prasad also contributes to the ABI’s cardiac mechanics and lung research and the development of high-performance computational physiology modelling software.

Research | Current

Biomechanics for breast cancer imaging

Addressing clinical challenges involved in diagnosing and treating breast cancer by melding biomechanics, state-of-the-art image processing techniques, and population based statistical analysis. My work has led to the development of a clinical workflow that automatically builds personalised biomechanical models of the breast from diagnostic medical images, and predicts breast tissue motion during breast cancer diagnosis and treatment procedures. We are now trailing this workflow at Auckland City Hospital. Learn more about this research at the ABI's Biomechanics for Breast Imaging group project page.

Cardiac mechanics

Developing automated computational modelling worflows for predicting patient-specific cardiac mechanics to identify novel biomarkers for early detection of diseases such as heart failure. Learn more about this research on the ABI Cardiac mechanics project page.

Understanding the passive and active behaviour of cardiac muscles using computational models paired with rich experimental data from ABI's novel cardiac instrumentation devices.

Parameter estimation, design of experiments, and uncertainty quantification

Creating and validating frameworks for identifying the mechanical properties of soft tissues using noninvasive methods. The models are complemented with novel instrumentation and imaging techniques that we are currently developing in the ABI Bioinstrumentation Laboratory to create rich experimental datasets that can maximise identifiability of the mechanical properties.

Lung modelling

Developing novel real-time full-field stereoscopic imaging systems for tracking lung surface deformation during ventilation. The rich experimental data obatined from these imaging systems provides the information required for quantifying the stress-strain behaviour of alveoli during early maturity and senescence. 

Developing multi-scale computational models of the lung that use this novel experimental data to better understand the mechanisms behind decline in lung function with aging. These models will help guide the development of new diagnostic methods to distinguish age related changes from lung disease.

Learn more about this research at the ABI's Lungs and Respiratory System project page.


Project links

Teaching | Current

BIOMENG 321 - Continuum Modelling in Bioengineering

Areas of expertise

  • construction of patient-specific biomechanical models

  • computational mechanics

  • finite element analysis

  • soft tissue modelling

  • statistical shape analysis

  • stereovision

  • medical image processing & registration

  • soft-tissue constitutive parameter estimation

  • design of experiments techniques

  • high performance computing software development

Selected publications and creative works (Research Outputs)

As of 29 October 2020 there will be no automatic updating of 'selected publications and creative works' from Research Outputs. Please continue to keep your Research Outputs profile up to date.
  • Maso Talou, G. D., Babarenda Gamage, T. P., Sagar, M., & Nash, M. P. (2020). Deep Learning Over Reduced Intrinsic Domains for Efficient Mechanics of the Left Ventricle. Frontiers in Physics, 810.3389/fphy.2020.00030
    Other University of Auckland co-authors: Gonzalo Maso Talou, Martyn Nash
  • Wang, Z. J., Wang, V. Y., Babarenda Gamage, T. P., Rajagopal, V., Cao, J. J., Nielsen, P. M. F., ... Nash, M. P. (2020). Efficient estimation of load-free left ventricular geometry and passive myocardial properties using principal component analysis. International journal for numerical methods in biomedical engineering10.1002/cnm.3313
    Other University of Auckland co-authors: Christopher Bradley, Vicky Wang, Poul Nielsen, Alistair Young, Martyn Nash
  • Babarenda Gamage, T. P., Malcolm, D. T. K., Maso Talou, G., Mîra A, Doyle, A., Nielsen, P. M. F., & Nash, M. P. (2019). An automated computational biomechanics workflow for improving breast cancer diagnosis and treatment. Interface focus, 9 (4)10.1098/rsfs.2019.0034
    Other University of Auckland co-authors: Martyn Nash, Anthony Doyle, Poul Nielsen, Gonzalo Maso Talou
  • Parker, M. D., Babarenda Gamage, T. P., HajiRassouliha, A., Taberner, A. J., Nash, M. P., & Nielsen, P. M. F. (2019). Surface deformation tracking and modelling of soft materials. Biomechanics and modeling in mechanobiology, 18 (4), 1031-1045. 10.1007/s10237-019-01127-3
    URL: http://hdl.handle.net/2292/49611
    Other University of Auckland co-authors: Andrew Taberner, Poul Nielsen, Martyn Nash
  • Babarenda Gamage, T. P., Rajagopal, V., Ehrgott, M., Nash, M. P., & Nielsen, P. M. F. (2011). Identification of mechanical properties of heterogeneous soft bodies using gravity loading. International Journal for Numerical Methods in Biomedical Engineering, 27 (3), 391-407. 10.1002/cnm.1429
    Other University of Auckland co-authors: Martyn Nash, Poul Nielsen


Contact details

Primary office location

Level 7, Room 719
New Zealand

Web links