Computational models are essential for assessing quantities that are
otherwise immeasurable. In general, my work focuses on the design
of large-scale parallel applications targeting problems in physics. I
design large-scale parallel applications that
enable the study of research problems in areas ranging from
cardiovascular disease to wireless networks to drug development.
The recognition of the role hemodynamic forces have in the localization and development of disease has motivated large-scale efforts to enable patient-specific simulations. When combined with computational approaches that can extend the models to include physiologically accurate hematocrit levels in large regions of the circulatory system, these image-based models yield insight into the underlying mechanisms driving disease progression and inform surgical planning or the design of next generation drug delivery systems. The scale of these simulations requires the use of massively parallel supercomputers, so much of my work involves the development of methods to maximize parallel efficiency. Through funding provided by my recent NIH Early Independence Award, I am expanding the scope of projects to address not only vascular diseases, but also treatment planning and the movement of circulating tumor cells in the bloodstream. Predicting the location of secondary tumor sites is a critical hurdle in the understanding and treatment of cancer. The goal of this research is to develop a method of predicting likely sites of cancer metastasis using a combination of personalized massively parallel computational models and experimental approaches.
News:Amanda has accepted a position as an Assistant Professor in Biomedical Engineering at Duke University. She will be starting there in July, 2015. Duke Press Release.
June 2, 2015. The following work was award Best Paper at the International Conference on Computational Science (ICCS):
A. Randles, E.W. Draeger, and P.E. Bailey. "Massively Parallel Simulations of Hemodynamics in the Human Vasculature." Journal of Computational Science 9 (2015): 70-75.
I am looking for highly motivated students to join my lab at Duke University. Interested students should contact me at firstname.lastname@example.org for more information.
I am currently seeking to hire several postdoctoral researchers in the areas of biofluid modeling and high performance computing. Candidates should have relevant research experience and hold a Ph.D. in Physics, Biomedical Engineering, Mathematics, Computer Science, or another related field. Applicants should send a cover letter, CV, and list of references as a single document to email@example.com.
Where will I be?
Quantitative Biology: From Molecules to Man, New York, NY on June 18, 2015.