Information Fusion has evolved from combining observations across multiple sensors to enabling intelligent systems that perceive, understand, predict, decide, and act in complex, uncertain, and dynamic environments.  As autonomous systems, artificial intelligence, foundation models, and human-AI collaboration continue to advance, information fusion has become a foundational discipline connecting sensing, learning, reasoning, and decision-making across physical, cyber, biological, and social domains.

FUSION 2027 invites original contributions spanning the full spectrum of information fusion, encompassing all levels of the Joint Director of Laboratories (JDL) Information Fusion Model, from signal and feature processing through object assessment, situation understanding, decision support, mission management, and adaptive sensing, as well as emerging paradigms integrating sensing, learning, reasoning, and autonomous decision-making.  The conference welcomes theoretical advances, algorithmic innovations, system architectures, experimental studies, and transformative real-world applications.  Contributions spanning multiple JDL levels and demonstrating end-to-end information fusion capabilities are especially encouraged.  Papers must be positioned and relevant to data/information fusion.