Reuben Tan

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About

Reuben Tan is a leading researcher in multimodal AI, with a focus on building foundation models that bridge vision, language, and autonomous agency. His most notable contribution is **Magma**, a foundation model designed for multimodal AI agentic tasks in both digital and physical environments. Magma extends traditional vision-language (VL) models by equipping them with the ability to plan and execute actions—what Tan terms "spatial-temporal and temporal-action intelligence." This work, published in 2025, has already garnered 19 citations, signaling its rapid impact on the field of embodied AI and autonomous systems. Tan’s research addresses a critical gap: enabling AI to not only understand but also act in the world. By integrating verbal and agentic intelligence, his work paves the way for more capable robots, virtual assistants, and interactive systems. For students and researchers, Tan’s contributions represent a frontier in AI—where models move beyond passive understanding to active, goal-driven behavior in complex, real-world settings.