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About

Corban G. Rivera is a robotics and artificial intelligence researcher whose work sits at the intersection of scene understanding, human-robot teaming, and autonomous planning. He is perhaps best known as a contributor to **ConceptGraphs**, a landmark framework that constructs open-vocabulary 3D scene graphs by integrating large vision-language models with spatial representations — enabling robots to perceive and plan across diverse, semantically rich environments. The work has garnered nearly 200 citations, underscoring its significant influence on the field of robot perception. Beyond scene representation, Rivera has made meaningful contributions to socially aware robot navigation, developing group-aware navigation policies that model the collective dynamics of pedestrians rather than treating individuals in isolation. His research in human-robot teaming explores how symbolic and subsymbolic AI can be integrated to create transparent, trustworthy collaborative systems. More recently, his work on ConceptAgent demonstrates a growing interest in leveraging large language models for robust task planning and execution in open-world settings. Across imitation learning, meta-learning, and multi-agent coordination, Rivera consistently pursues robots that are not merely functional, but genuinely adaptable partners — capable of learning generalizable behaviors and operating fluidly alongside humans in complex, real-world environments.