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Hi there 👋, I'm Théo Duez

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🎓 PhD student in applied mathematics, with a background in mathematics, and scientific computing.

🔬 Research Interests : Numerical analysis, PDEs, Quantum physics, Time-dependant density functional theory (TDDFT)

💻 Programming Languages :

Julia C++ Python Python

Selected projects

  • CEA Saclay — Nov 2022 → Mar 2023 : Lattice Boltzmann simulations for two-phase flows with d evelopment within the LBM_saclay C++ code.

  • Max Planck Institute — Apr 2023 → Aug 2023 : Physics-informed neural networks (PINNs), in particular Symplectic, Hamiltonian and Lagrangian neural networks (SympNet, HNN, LNN). In contributed mostly to the Julia package GeometricMachineLearning.jl.

  • CNRS, Cermics — May 2024 → Today : Simulation of the groundstate of atoms and ions in the extended-Kohn Sham formalism. See AtomicKohnSham.jl.

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