Rishit Dagli
I am interested in learning algorithms, computer vision, graphics, learning theory, and math. My work builds models that can produce physically realistic dynamic worlds as well as understand/interact with our world.
Currently, I’m a research intern at . I am an undergraduate student in CS and Math at
University of Toronto. Previously, I took a 1-year break from my undergrad to work at
as a research intern at the intersection of AI, vision, and graphics. Before that, I was a research intern at
AI Research with Roland Memisevic, Guillaume Berger on video-audio-language models (VLMs). Even before that, I was a research engineering intern at
with Josh Mesout where I focused on improving inference performance of multimodal models.
In a past life, I used to work on software engineering and building robot hardware. I used to contribute to some popular open-source software.
selected publications
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Squeeze3D: Extreme Neural Compression with Latent Space Bridging
TMLR 2026 -
Adaptive Volumetric Mechanical Property Fields Invariant to Resolution
ICML 2026 -
RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
RSS 2026 (Oral) -
FreeForm: Reduced-Order Deformable Simulation from Particle-Based Skinning Eigenmodes
CVPR 2026 (* joint first authors)press:SIGGRAPH Hands-On Lab -
VoMP: Predicting Volumetric Mechanical Property Fields
ICLR 2026 -
Can Vision-Language Models Answer Face to Face Questions in the Real-World?
ICLR 2026 (* joint first authors)press:Thinking Machines Lab -
SEE-2-SOUND: Zero-Shot Spatial Environment-to-Spatial Sound
SIGGRAPH Posters 2025