Yulia Rubanova is a Staff Research Scientist at Google DeepMind with 10 years of experience building physically grounded world models and real-time video generative systems. She co-led and was a core contributor to Veo Ingredients, helping ship Veo3.1 features including audio and enhanced character consistency showcased at Google I/O 2025. Her PhD work on Neural ODEs and Latent ODEs informs her approach to modeling continuous-time dynamics and controllable simulations for complex objects and environments. Yulia’s research spans controlling objects in image generation to learning 3D physical simulations, with a focus on moving generation toward interactive simulation for robotics, autonomous driving, and storytelling tools. Based in London, she blends deep theoretical expertise with product-impacting engineering at scale. An unexpected thread across her career is applying probabilistic and continuous-time methods—from genomics and cancer evolution to video synthesis—to make models both interpretable and controllable.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Toronto
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Yulia Rubanova - Staff Research Scientist at Google DeepMind