Sarah Vallélian


I am a postdoctoral researcher at North Carolina State University. My appointment is joint with the Statistical and Applied Mathematical Sciences Institute (SAMSI), where I was affiliated with the 2015-16 annual program on Challenges in Computational Neuroscience.

Broadly speaking, my research interests are in inverse problems with PDEs, numerical analysis, and medical imaging. Currently I am working with Arvind Saibaba on computational aspects of deterministic and statistical inverse problems, namely dimension reduction. My dissertation work was on optimization and uncertainty quantification in photoacoustic tomography.


Computationally efficient Markov Chain Monte Carlo methods for hierarchical Bayesian inverse problems

D. A. Brown, A. K. Saibaba and S. Vallélian. In revision. arxiv:1609.07180

A one-step reconstruction algorithm for quantitative photoacoustic imaging

T. Ding, K. Ren and S. Vallélian. 2015 Inverse Problems 31 095005.

Work in progress:


I love talking about and sharing mathematics and am always interested to learn new methods or resources for effective teaching.

Teaching at NCSU:

Other Activities:

I gave a tutorial on X-ray Computed Tomography at the SAMSI CCNS Undergraduate Workshop in October 2015. Here are the resources:

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).

For details about my past teaching experiences take a look in my CV.



You can view my CV here.

I am also on Linkedin. My current email address is below.