Sarah Vallélian

Sarah VallelianI am a second year postdoc affiliated with the Challenges in Computational Neuroscience program. My supervisor is Arvind K. Saibaba in the Mathematics Department at NC State University. My research is in the theory and computation of inverse problems with partial differential equations, particularly photoacoustic tomography (PAT) and related multi-physics biomedical imaging modalities. I am currently investigating reduced order models for multispectral PAT, where realistic high-resolution small animal brain images may contain up to a million voxels and measurements may be desired at hundreds of wavelengths. I am also interested in applying efficient sampling strategies such as multilevel MCMC for quantifying uncertainty in real neuroimaging data, such as fMRI images or EEG/MEG signals.

I am excited to be learning something very new at SAMSI, studying neuromechanical processes in Laura Miller and Katie Newhall’s working group. I hope to make some contributions towards developing an integrative model for insect walking, including realistic muscle contractions and dynamic limb-surface interaction.

I earned my PhD in Mathematics from UT Austin in May 2015. Here is my old webpage, which is still moderately up to date.

My CV is available here.

I gave a tutorial on X-ray Computed Tomography at the SAMSI CCNS Undergraduate Workshop in October 2015. Here are the slides; code and documentation is available on my old website. This tutorial draws on materials from the UW RTG I attended in 2011. In particular some codes by François Monard were used in the demo, and the notes by François Monard and Steve McDowall are recommended as additional references (available here).