I am a Research and Development Scientist at Ubisoft La Forge. Ubisoft La Forge (i.e., Ubisoft R&D lab) brings experts from both the industry and academic sector to bridge the gap between theoretical research and game-making process, while contributing to solving real-world problems through scientific publications. At La Forge, I investigate new methods to enhance our virtual worlds with plausible, interactive, and art-directable physics / FX.
Prior to joining Ubisoft, I was a PhD candidate in Computer Science in both Université de Montréal ( LIGUM laboratory) and Université de Poitiers ( XLIM laboratory), where my advisors were Pr. Pierre Poulin and Pr. Philippe Meseure. My past experiences include natural phenomenon modeling, physics-based animation and procedural generation. In general, I have a broader interest in real-time graphics and artistic control.
Ph.D. in Computer Science, 2021
Université de Montréal / Université de Poitiers
MAE, General Management, 2016
Institut d'Administration des Entreprises de Caen
M.Sc. in Computer Science, 2016
Ecole Nationale Supérieure d'Ingénieurs de Caen
Poisson equations appear in many graphics settings including, but not limited to, physics-based fluid simulation. We propose a new Poisson filter-based solver that balances between the strengths of spectral and iterative methods. We derive universal Poisson kernels for forward and inverse Poisson problems, leveraging careful adaptive filter truncation to localize their extent, all while maintaining stability and accuracy.
Physics-based animation can generate dynamic systems of very complex and realistic behaviors. Unfortunately, controlling them is a daunting task. In particular, fluid simulation brings up particularly difficult problems to the control process. This thesis presents two projects. First, we introduce a new particle-based liquid control system based on precomputed liquid animations. Second, a tracking solution for smoke upresolution is described.
It is notoriously difficult for artists to control liquids while generating plausible animations. We introduce a new liquid control tool that allows users to load, transform, and apply precomputed liquid simulation templates in a scene in order to control a particle-based simulation.
Controlling smoke simulations is a notoriously challenging and tedious task. We propose a tracking procedure where we optimally modify the velocity field of the simulation in order to make the smoke density distribution closely follow the low-resolution density in both space and time.