I'm a master's student in fluid mechanics at Institut Polytechnique, and most of what I do comes back to a single loop: take something physical (air over a wing, a pressure wave, turbulence), and turn it into a measurement, then a CFD simulation, then code, then something you can build with. That's what I did last summer at ONERA, where my research internship applied tensor-network methods to computational fluid dynamics, making the Lattice-Boltzmann method more efficient. Around it sits a growing pile of smaller experiments: a Pitot probe wired to an Arduino, a hot-wire anemometer in progress, and a Mathematica library for the tensor-train math underneath it all.

I like the part where theory meets a soldering iron, where a model has to survive contact with real hardware, real data, and a deadline. I'm also a founding member of École Polytechnique's IEEE student branch. Whether it's a CFD solver that has to run faster or an instrument that has to actually measure something, I care most about the point where the physics becomes something that works.

Off the screen, I skydive. Fluids, again. I just prefer them at speed.