Raul P. Pelaez

I’m a physicist, research software engineer, and consultant specializing in GPU high-performance computing, simulation of complex systems, and machine learning for the physical sciences.
With over a decade of experience at the interface of physics, computer science, and biology, I help research teams and companies develop robust, high-performance software for scientific discovery. My background includes a Ph.D. in Physics from Universidad Autónoma de Madrid, postdoctoral research at New York University and Universitat Pompeu Fabra, and teaching at IE University.
I’ve contributed to major open-source simulation platforms like OpenMM, TorchMD-NET, and UAMMD, and have led projects involving GPU acceleration, fluctuating hydrodynamics, and neural network potentials. Whether building custom simulation pipelines, optimizing molecular dynamics code, or designing machine learning integrations, I bring a pragmatic, research-savvy approach to scientific software challenges.
As a freelance consultant, I offer mentoring and training in scientific programming best practices, as well as custom development of high-performance scientific software.
If you’re working on a scientific or technical problem that needs fast, reliable, and scalable code, let’s talk.
Contact
Send me an email to contact@raulppelaez.com
Trusted by
These are some of my previous and ongoing collaborations.
Selected publications
- A fast spectral method for electrostatics in doubly periodic slit channelsThe Journal of Chemical Physics, 2021
- OpenMM 8: molecular dynamics simulation with machine learning potentialsThe Journal of Physical Chemistry B, 2023
- Universally Adaptable Multiscale Molecular Dynamics (UAMMD). A native-GPU software ecosystem for complex fluids, soft matter, and beyondComputer Physics Communications, 2025
- Spectral solver for the oscillatory Stokes frequency-based equation in doubly periodic confined domainsJournal of Fluid Mechanics, 2025