Carina
Suciu has joined the Stochastic Numerics Group and SRI Uncertainty
Quantification Center at KAUST. Carina is an Applied Mathematician
and Computational Scientist specializing in numerical methods solving
Populations Balance Systems (PBS). In 2007 she started to work in
cooperation with chemical engineers and industrial partners, in the
framework of a project “Coupled Simulations of Particle Populations
in Turbulent Flows”. She was engaged in in the analysis,
development and implementation of numerical algorithms for problems
arising, e.g. crystallization. Such systems can be modeled with PBS
which are coupled systems of Navier-Stokes equations to describe the
flow field, convection-diffusion equations to describe transport for
temperature and concentration and transport equations for the
particle size distribution (PSD).
She
earned diploma degree (2001) in Mathematics at Universitatea de Vest
Timisoara, Romania, and a Ph.D. (2013) in Applied Mathematics at the
Free University of Berlin, working in the group of Prof. John at
Weierstarss Institute for Applied Analysis and Stochastics, Germany.
Her
Ph.D. research focus was numerical schemes for uni- and bi-variate
PBS, in particular so-called direct discretization. In direct
discretization, the higher-dimensional transport equation for the PSD
(space + internal coordinates), is discretized directly in
higher-dimensional domain.
From
2014-2016 she was a Postdoctoral Researcher at Weierstrass Institute
for Applied Analysis and Stochastics in Germany. In the framework of
the project “Erforschung Effizzienter mathematische Methoden zur
Modellkaliebrirung und Unbestimmtheiabschätzung in
Umweltsimulationen” which was also a joint work with an industrial
partner (DHY-WASY), she became also interested in numerical methods
for Uncertainty Quantification in subsurface flow.
Her
research interests lie in both deterministic and stochastic numerical
methods for partial differential equations with applications in
various engineering area. Currently, in collaboration with École
polytechnique fédéral de Lausanne (EPFL) and National University of
Singapore (NUS), she
is interested in developing modern and efficient techniques for
Forward and Inverse Problems in Uncertainty Quantification.
https://sri-uq.kaust.edu.sa/Pages/CarinaSuciu.aspx