Iro Armeni

Iro Armeni is an Assistant Professor of Civil and Environmental Engineering at Stanford University. Her research interests include interdisciplinary work at the intersection of Architecture, Civil Engineering, and Visual Machine Perception. She focuses on developing data-driven methods to generate, predict, and simulate built environments that prioritize human needs. Armeni's work explores the integration of physical and digital spaces through Mixed Reality. She completed her PhD at Stanford University in 2020 with a minor in Computer Science and was a Postdoctoral Fellow at ETH Zurich (2023). Prior to her PhD, she earned an MSc in Computer Science from Ionian University (2013), an MEng in Architectural Engineering from the University of Tokyo (2011), and a Diploma in Architectural Engineering from the National Technical University of Athens (2009).

Iro Armeni is a researcher at Stanford University focusing on 3D scene understanding and semantic parsing of indoor spaces. Their work explores advanced techniques for 3D semantic segmentation, including the development of systems for semantic segmentation of 3D point clouds and 3D scene graph representation. Armeni's research also addresses challenges in automatic as-built modeling, 3D point cloud registration, and scene alignment using scene graphs. They have contributed to the development of methods for multi-object relocalization in dynamic environments and have explored the integration of language with scene retrieval. Their research emphasizes the use of 3D Gaussian splats and diffusion models for robust scene understanding and navigation.