I am a Senior Solution Architect for DevitoCodes where I am one of the main developers for Devito and its commercially licensed extension devitopro. I have been working for the past decade on scalable and portable open-source software for exploration geophysics and inverse problems. This allowed me to develop my skills in programming in both Python and Julia and get familiar with Cloud computing on AWS and Azure.

My research interest and software development skills range from applied mathematics to exascale HPC. My current interests include:

• Machine learning: I am working on computational methods for machine learning such as the application of randomized linear algebra methods.

• HPC: Our lab focuses mainly on HPC for task parallel exascale problems such as photoacoustic or seismic imaging.

• DSLs:

  • I am one of the primary developers of Devito, in particular of its symbolic APIs.
  • Main developer of JUDI a linear algebra DSL for PDE constraints optimization built on top of Devito

• PDE-constrained optimization and inverse problems: Methods and Algorithms for wave-equation-based inverse problems such as photoacoustic and ultrasound imaging (medical) or subsurface imaging (sexploration geophysics).

• Cloud computing: I have been working on developing large-scale algorithms running on conventional clusters and in the cloud (AWS, Azure, ...)

• 📫 How to reach me: mathias.louboutin@gmail.com