Syver Døving Agdestein

Appearance

Curriculum Vitae ​

Employment ​

2025–Present
Postdoctoral researcher
Scientific Computing group, CWI · Amsterdam, the Netherlands
2021–2025
PhD researcher
Scientific Computing group, CWI · Amsterdam, the Netherlands
2020–2021
Software Engineer
INRIA / École Polytechnique · Palaiseau, France
6-month position
2020
Research intern
IRT Saint Exupéry · Toulouse, France
Multidisciplinary optimization · 6 months

Education ​

2021–2026
PhD in applied mathematics cum laude
Eindhoven University of Technology · the Netherlands
Thesis: Data-driven discrete closure models for large-eddy simulation of incompressible turbulence (research carried out at CWI, Amsterdam)
2015–2020
MSc / Diplôme d'Ingénieur, applied mathematics
INSA Toulouse · France
2018–2019
Exchange year
Peter the Great St. Petersburg Polytechnic University · Saint Petersburg, Russia
Theoretical mechanics and applied mathematics
2012–2015
Asker Upper Secondary School
Norway
2013–2014
Exchange year
Collège Saint-Guibert · Gembloux, Belgium

Software ​

Publications ​

Time integration as filtering: a space-time discretization-aware LES formulation
Time integration as filtering: a space-time discretization-aware LES formulation
Syver Døving Agdestein · arXiv preprint · 2026
preprintcode
Data-driven discrete closure models for large-eddy simulation of incompressible turbulence
Data-driven discrete closure models for large-eddy simulation of incompressible turbulence
Syver Døving Agdestein · PhD thesis · 2026
thesis
A differentiable software suite for accelerated simulation of turbulent flows
A differentiable software suite for accelerated simulation of turbulent flows
Syver Døving Agdestein and Benjamin Sanderse · arXiv preprint · 2026
preprintcode
Comparison of Data-Driven Symmetry-Preserving Closure Models for Large-Eddy Simulation
Comparison of Data-Driven Symmetry-Preserving Closure Models for Large-Eddy Simulation
Syver Døving Agdestein and Benjamin Sanderse · arXiv preprint · 2026
preprintcode
Exact Expressions for the Unresolved Stress in a Finite-Volume Based Large-Eddy Simulation
Exact Expressions for the Unresolved Stress in a Finite-Volume Based Large-Eddy Simulation
Syver Døving Agdestein, Roel Verstappen, and Benjamin Sanderse · Journal of Computational Physics 556 · 2026
paperpreprintcode
A New Data-Driven Energy-Stable Evolve-Filter-Relax Model for Turbulent Flow Simulation
A New Data-Driven Energy-Stable Evolve-Filter-Relax Model for Turbulent Flow Simulation
Anna Ivagnes et al. · Computer Methods in Applied Mechanics and Engineering 450 · 2026
paperpreprint
Discretize First, Filter next: Learning Divergence-Consistent Closure Models for Large-Eddy Simulation
Discretize First, Filter next: Learning Divergence-Consistent Closure Models for Large-Eddy Simulation
Syver Døving Agdestein and Benjamin Sanderse · Journal of Computational Physics 522 · 2025
paperpreprintcode
Discretize First, Filter next – a New Closure Model Approach
Discretize First, Filter next – a New Closure Model Approach
Syver Døving Agdestein and Benjamin Sanderse · 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) · 2022
paperpreprintcode
Practical Computation of the Diffusion MRI Signal Based on Laplace Eigenfunctions: Permeable Interfaces
Practical Computation of the Diffusion MRI Signal Based on Laplace Eigenfunctions: Permeable Interfaces
Syver Døving Agdestein, Try Nguyen Tran, and Jing-Rebecca Li · NMR in Biomedicine 35.3 · 2022
papercode
Artery.FE: An Implementation of the 1D Blood Flow Equations in FEniCS
Artery.FE: An Implementation of the 1D Blood Flow Equations in FEniCS
Syver Døving Agdestein, Kristian Valen-Sendstad, and Alexandra Diem · Journal of Open Source Software 3.32 · 2018
papercode

Contributed talks ​

Data-driven discrete closure models for large-eddy simulation of incompressible turbulence
Data-driven discrete closure models for large-eddy simulation of incompressible turbulence
Bernoulli Institute Seminar · Groningen, the Netherlands · July 2, 2026
Are we modeling the wrong stress tensor in LES?
Are we modeling the wrong stress tensor in LES?
ERCOFTAC DLES · Delft, the Netherlands · May 21, 2026
slideswebpage
Data-driven discrete closure models for large-eddy simulation of incompressible turbulence
Data-driven discrete closure models for large-eddy simulation of incompressible turbulence
KWG afternoon session · Amsterdam, the Netherlands · May 8, 2026
slideswebpage
Symmetry-preserving LES: Comparison of data-driven closure models
Symmetry-preserving LES: Comparison of data-driven closure models
ERCOFTAC ML4FLUIDS · Amsterdam, the Netherlands · March 2026
slideswebpage
Data-driven closure modeling: From deterministic to probabilistic models
Data-driven closure modeling: From deterministic to probabilistic models
INRIA SPADES associate team meeting · Rome, Italy · December 2025
slides
Should structural turbulence closures be non-symmetric?
Should structural turbulence closures be non-symmetric?
SCS Spring Meeting · Hasselt, Belgium · June 2025
webpage
Model-data consistent closure models in large-eddy simulation
Model-data consistent closure models in large-eddy simulation
SIAM CSE · Fort Worth, USA · February 2025
abstractwebpage
Model-data consistent closure models in large-eddy simulation
Model-data consistent closure models in large-eddy simulation
DTE & AICOMAS · Paris, France · February 2025
Discrete closure models for turbulent flows: Exploiting differentiable programming
Discrete closure models for turbulent flows: Exploiting differentiable programming
Meetup of the NL-RSE Community · Amsterdam, the Netherlands · November 2024
Discretize first, filter next: Learning divergence-consistent closure models for large-eddy simulation
Discretize first, filter next: Learning divergence-consistent closure models for large-eddy simulation
ECCOMAS · Lisbon, Portugal · June 2024
Learning neural closure models for discretely filtered turbulence
Learning neural closure models for discretely filtered turbulence
ERCOFTAC ML4FLUIDS · Paris, France · March 2024
Closure models for discretely filtered differential equations
Closure models for discretely filtered differential equations
CFC · Cannes, France · April 2023
Closure models for discretely filtered differential equations
Closure models for discretely filtered differential equations
Seminar, Bernoulli Institute for Mathematics, Groningen University · Groningen, the Netherlands · February 2023
Closure models for discretely filtered differential equations
Closure models for discretely filtered differential equations
SIAM CSE · Amsterdam, the Netherlands · February 2023
Data-driven filtering of differential equations
Data-driven filtering of differential equations
ECCOMAS · Oslo, Norway · June 2022

Teaching & supervision ​

  • Supervised Master's theses:
    • Lucas Ronckers, Probabilistic turbulence modeling with ideal large eddy simulation: Bayesian inverse filtering and flow matching (2026)
    • Viviane Desgrange, An inverse problem approach for closure modelling (2023)
  • Lectures at schools and masterclasses:
    • Learning neural closure models for fluid flows — Autumn School on Scientific Machine Learning, CWI (October 2023)
    • Learning physics from data — Masterclass on Machine Learning for Inverse Problems: A Bayesian Perspective, CWI (May 2022)

Service & outreach ​

  • Peer review: Journal of Computational Physics
  • CWI works council (2023–2025)