I am a PhD candidate at ETH Zurich (NANO-TCAD), specializing in High-Performance Computing (HPC) and scalable numerical methods for large-scale scientific applications. My research focuses on GPU-accelerated linear solvers, Bayesian inference frameworks, and nanoscale quantum transport simulations.
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Currently developing:
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Skills & Expertise:
- High-Performance Computing: MPI, OpenMP, CUDA, OpenACC, distributed memory algorithms, GPU computing, performance optimization
- Numerical Methods: Sparse linear algebra, selected inversion, iterative & direct solvers, numerical optimization
- Scientific Applications: Quantum transport simulations (NEGF), Bayesian inference (INLA), spatio-temporal modeling, mechanical smart-structures
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Contact: vmaillou@iis.ee.ethz.ch
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LinkedIn: vincent-maillou
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GitHub: vincent-maillou
- PhD, ETH Zurich – Selected Linear Solvers for Scientific Applications (2023–Present)
- Master's Degree, Centrale Nantes (2018–2022)
- Preparatory Classes TSI, Lycee Jean Perrin (2015–2018) – Laureate
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NVIDIA DLI Certificate – Fundamentals of Accelerated Computing with CUDA C/C++
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NVIDIA DLI Certificate – Accelerating CUDA C++ Applications with Concurrent Streams
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- Ab-initio Quantum Transport with the GW Approximation, 42,240 Atoms, and Sustained Exascale Performance – N. Vetsch, A. Maeder, V. Maillou, et al., 2025
- Accelerated Spatio-Temporal Bayesian Modeling for Multivariate Gaussian Processes – L. Gaedke-Merzhäuser, V. Maillou, F. R. Avellaneda, et al., 2025
- Serinv: A Scalable Library for the Selected Inversion of Block-Tridiagonal with Arrowhead Matrices – V. Maillou, L. Gaedke-Merzhaeuser, A. N. Ziogas, et al., 2025
- Mass-Spring Models for Passive Keyword Spotting: A Springtronics Approach – F. Bohte, T. Louvet, V. Maillou, et al., 2025
- Towards Exascale Simulations of Nanoelectronic Devices in the GW Approximation – L. Deuschle, A. Maeder, V. Maillou, et al., SC24, 2024
For full publications list, see my Google Scholar profile.
| Project | Description | GitHub |
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| Serinv | Selected solver library for structured sparse matrices; supports sequential and distributed-memory algorithms with GPU acceleration. | Link |
| DALIA | High-performance Python framework for approximate Bayesian inference, leveraging structured sparse solvers for spatio-temporal modeling. | Link |
| QuaTrEx | Quantum transport simulations using the non-equilibrium Green's function formalism at exascale HPC. | Link |
| Stats | Top Languages | Streak |
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