CV
Basics
| Name | Raúl Pérez Peláez |
| contact@raulppelaez.com | |
| Summary | I specialize in high-performance scientific software and machine learning for physical sciences. I build robust, GPU-accelerated simulation tools and consult on projects that demand deep integration of physics, software engineering, and modern ML techniques. |
Languages
| English | |
| Fluent |
| Spanish | |
| Mother tongue |
Skills
| Guru | |
| C++20 | |
| CUDA | |
| Python | |
| PyTorch | |
| UNIX | |
| emacs | |
| CMake | |
| git |
| Advanced | |
| Regex | |
| SYCL | |
| Latex | |
| OpenMP | |
| OpenGL 3.3+ | |
| C | |
| Matlab | |
| WebAssembly | |
| WebGPU | |
| WebGL | |
| Numba |
| Intermediate | |
| Perl | |
| MPI | |
| Java | |
| SDL2 | |
| inkscape | |
| gimp | |
| Arduino | |
| gdb | |
| SFML | |
| OpenCL | |
| JAX | |
| Javascript/Typescript |
| Basic | |
| Android | |
| Fortran | |
| PowerShell | |
| Triton | |
| WebUSB | |
| TinyGrad | |
| React |
| DevOps tools | |
| GitOps | |
| CI/CD (GitHub Actions) | |
| Docker/Compose | |
| pip | |
| conda | |
| npm | |
| SLURM | |
| Ansible |
| Software Engineering | |
| Hygienic software engineering principles applied to projects of any size from the ground up |
Interests
| High performance scientific computing and GPU programming |
| DevOps |
| Software engineering |
| Machine learning |
| Modeling and simulation of biological systems |
| Complex fluids and fluctuating hydrodynamics |
Work
-
2026 - Present -
2025 - 2026 Research scientist
Universidad Autónoma de Madrid
- Developed several GPU-ready open source tools for high-performance scientific computing (C++/CUDA with Python wrappers)
- Set up CI/CD GitHub actions with custom runners for automatic testing and benchmarking in a local GPU cluster (~100 GPUs)
- Developed new massively parallel algorithms for biosensor modelling, published in scientific journals
- Wrote a high-performance web application (WebAssembly via C++ with Emscripten, WebGPU, Astro/React) for a digital twin product
- Developed and implemented high-performance algorithms for research in liquid memory storage
- Mentored several PhD students
-
2024 - Present Adjunt professor
IE University
- Lecturer (Adjunct) in the Computer Science and Applied Math degrees
- Computer Programming 2 (compsci): C++
- Computer Programming 2 (applied math): Advanced Python
- Computer Programming 1 (compsci): Advanced C
-
2023 - 2024 Research director
Universitat Pompeu Fabra (UPF)
- Provided GPU libraries and tooling for AI-assisted molecular modeling and drug discovery
- Optimized TorchMD-Net (50x speed-up)
- Maintained conda-forge ecosystem packages
- Integrated CUDA Graphs into OpenMM-Torch
- Built GPU-enabled CI/CD systems
- Developed internal LLM assistant running on in-house GPU cluster
- Finetuned LLM models for drug discovery workflows
-
2022 - 2023 Postdoctoral researcher
Universidad Autónoma de Madrid
- Research software engineer and postdoctoral researcher
- Managed SLURM HPC cluster with 600 CPUs and 40 GPUs
-
2021 - 2022 Postdoctoral research assistant
New York University (Courant Institute)
- Worked with Prof. Aleksandar Donev
- Specialized in GPU HPC software for fluctuating hydrodynamics
-
2018 - 2021 Ph.D. student
Universidad Autónoma de Madrid
- Developed GPU algorithms for complex fluids and colloidal systems
-
2015.05 - 2017 Software technician
Universidad Autónoma de Madrid
- Developed high performance GPU software for molecular dynamics
- Focused on complex fluids and colloids
- Worked on simulation and visualization