About me

Short Bio

I obtained my PhD degree in Computational Science in 2022 at University of Amsterdam, under the supervision of Prof. Alfons Hoekstra. My PhD work mainly focused on surrogate modelling and uncertainty quantification for a multi-scale simulation, in-stent restenosis model, as a part of Horizon 2020 project, VECMA. The VECMA stands for Verified Exascale Computing for Multiscale Applications and aims to develop software tools in order to validate, verify, and quantify the uncertainty (VVUQ) on in-silico models from different disciplines. 

Before I started my PhD, I studied Simulation Science at RWTH Aachen University, mainly about numerical methods, high-performance computing and computational fluid dynamics. Meanwhile, I worked as Hiwi (research assistant) at the Institute of General Mechanics under the supervision of Dr. Franz Bamer on reduced-order modelling and finite element simulation for structural mechanics models. I did my master thesis on modelling oxygen transport of nephrons at Interface Group, University of Zurich under the supervision of Dr. Kartik Jain and Prof Vartan Kurtcuoglu. 

I finished my bachelor's degree in 2014 at Tongji University, majoring in Engineering Mechanics. Speaking of which, I really missed the food and canteen there 🤓

Recent talk

• 12/2023 - Gaussian process learning for nonlinear dynamics, Scientific Machine learning Workshop, Amsterdam, Netherlands .

• 09/2023 - Registration-based reduced-order modelling for blood flow simulation, Computational BioMedicine Conference 2023, Munich, Germany.

•  07/2023 - Non-intrusive reduced-order modelling with surface registration, Mathematics of Data Science Seminar, University of Twente, Enschede, Netherlands.

• 04/2023 - Uncertainty quantification and surrogate modelling of three-dimensional in-stent restenosis model, Lorentz Center Workshop: Uncertainty Quantification for Healthcare and Biological Systems, Leiden, Netherlands.

• 02/2023 - Non-intrusive reduced-order modelling for blood flow simulations with surface registration, SIAM Conference on Computational Science and Engineering 2023, Amsterdam, Netherlands

Teaching:

• Stochastic Simulation, University of Amsterdam (2019-2021)

Supervision:

• Konstantinos Kevopoulos, master’s thesis, UvA, co-advised with Prof Daan Crommelin
  Topic: kernel-based parametric dynamic mode decomposition for nonlinear dynamics  (ongoing)

• Cillian Hourican, master’s thesis, UvA, co-advised with Dr. Valeria Krzhizhanovskaya,
  Topic: non-intrusive uncertainty quantification of a 3D in-stent restenosis model with adaptive surrogate modelling (2021)

• Salome Kakhaia, master’s thesis, UvA, co-advised with Dr. Valeria Krzhizhanovskaya and Dr. Pavel Zun 
  Topic: inverse uncertainty quantification of a mechanical model of arterial tissue with surrogate modeling (2021)