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publications
Hierarchical Differentiable Fluid Simulation
Published in Computer Graphics Forum, 2025
Differentiable simulation is an emerging field that offers a powerful and flexible route to fluid control. In grid-based settings, high memory consumption is a long-standing bottleneck that constrains optimization resolution. We introduce a two-step algorithm that significantly reduces memory usage: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub-domains while maintaining differentiability. In trading runtime for memory, it enables optimization at previously unattainable resolutions. We validate its effectiveness and memory savings on a series of fluid control problems.
talks
teaching
Teaching Assistant - Realistic (& Advanced) Image Synthesis
Undergraduate course, McGill University, 2023
Teaching assistant for McGill’s ECSE 446/546 Realistic (& Advanced) Image Synthesis. In charge of conducting office hours, writing assignment handouts, and creating grading automation tools.