I am currently a Ph.D. candidate in Computer Science at the University of Montreal ( LIGUM laboratory ) and the University of Poitiers ( XLIM laboratory ), under the supervision of professors Pierre Poulin, Philippe Meseure and Emmanuelle Darles. My doctoral research focuses on both liquid and smoke simulation control and upresolution. My past experiences include natural phenomemon modeling and animation as well as procedural generation. In general I have a broader interest in physically based animation and real-time graphics.
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
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. Each template instance generates control forces that drive the global simulated liquid to locally reproduce the templated liquid behavior. Our system is augmented with a variable proportion of temporary particles to help efficiently reproduce the templated liquid density, with fewer requirements on the surrounding environment. The resulting control strategy adds only a small computational overhead, leading to quick visual feedback for resolutions allowing interactive simulation. We demonstrate the robustness and ease of use of our method on various examples in 2D and 3D.
Controlling smoke simulations is a notoriously challenging and tedious task, usually requiring many trial-and-error iterations that prevent using expensive computations at high resolutions. Unfortunately, naıvely going from a more efficient low-resolution simulation to a high-quality high-resolution simulation usually results in a different behavior of smoke animation. Moreover, the longer the animation, the more different the result. 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. We demonstrate the benefits of our approach by accurately tracking various 2D and 3D simulations. The resulting animations are predictable, preserving the coarse density distribution of the low-resolution guides, while being enhanced with plausible high-frequency details.