Hi, I’m Corentin Lapeyre. Born in Toulouse France, brought up between the south of France and Berkeley, CA, I feel at home both in Europe and the USA.

I have always been passionate about physics. After a scientific baccalaureate, I went to engineering school, and really loved it! I was lucky to participate in a student race car project. This confirmed my taste for technological challenges, especially by handling a project from start to finish: from computer-aided design and optimisation to organizing and overseeing the production. After that I decided to turn to aerospace engineering, and completed my masters in this field. After 6 months at Purdue University, I found an opportunity for a Ph.D. in numerical combustion physics in France, and I decided to go back. I defended my Ph.D. in September of 2015, and am now shifting towards artificial intelligence and how recent advances in this field can apply to physics, specifically numerical fluid dynamics, combustion, and the geophysics of natural reservoirs.

During the course of my studies, I have extensively used and learned about computer-aided design, as well as low and abstract level coding for scientific applications. I have worked with Fortran/MPI for High Performance Computing applications, but have now become more of a Python evangelist. I am a daily heavy user of git, vim and LaTeX on Mac OS and Unix platforms.

I was a research scientist for several years, working at the interface between academia and the industry. In my opinion, both can strongly benefit from each other. The industry can no doubt enjoy the added edge that most recent scientific advancements can provide. It might be less obvious, but I also think that the world of scientific computing has much to learn about industry standards and good practices, notably in the field of software. Open source is becoming ubiquitous in this area, as a tool for science and industry to work together. The field of machine learning and AI are leading the way in this sense, and part of my mission was to spread this practice to other fields of physics.

Recently, I’ve joined Nvidia to continue this work at the interface of academia and the industry. Specifically, I’m part of the Strategic Research Engagement team, which seeks to leverage opportunities to boost science with accelerated computing through deep technical collaborations with researchers across Europe.

Resume

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Positions

  • Feb 2024 - Present: Developer Relations - Researcher Engagement at Nvidia
  • March 2018 - Feb 2024: Research Scientist - AI for Physical Modeling at CERFACS
  • November 2016 - February 2018 : Postdoctoral fellow at CERFACS
  • May 2015 - October 2016 : Postdoctoral fellow at IMFT
  • 2012 - 2014 : Teaching assistant in physics at EIPurpan. Total of ~100 hours.
  • April - September 2011 : Research assistant at Purdue university
  • June - July 2010 : Research intern at LMFA
  • 2009 - 2010 : Translation from French to English of a fluid dynamics textbook
  • Up to 2009 : Several years of private tutoring (high-school level)

Education