Scholar
Iro Armeni
Google Scholar ID: m2oTZkIAAAAJ
Stanford University
Citations & Impact
Citations
5,187
H-index
14
i10-index
19
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Google Research Scholar Program (2025-26): Worldwide early-career faculty funding for research on Machine Perception; ETH Zurich Postdoctoral Fellowship (2020-22): University-level funding for postdoctoral studies on Machine Perception for Architecture, Construction, and Facility Management; Google Ph.D. Fellowship (2017-20): Competitive funding across North America and Europe, for Ph.D. studies on Machine Perception; Stanford CIFE Seed Research Award (2016-17): Department-level funding, for research on 'Automated Semantic Understanding of Buildings'; Stanford School of Engineering Fellowship, Rick & Melinda Reed Grad. Fellowship (2015-16): University-level funding, for Ph.D. studies; EU Marie-Curie Fellowship (2014-15): For the project 'Automated As-Built Modelling of the Built Infrastructure'; EU Marie-Curie Fellowship (2013-14): For the project 'BIMAutoGen'; Japanese Government Scholarship (MEXT) (2009-11): Competitive, nation-level funding, for MEng degree; Erasmus Scholarship (Jan-Jun 2007): The State Scholarships Foundation, EU, University-level funding, foreign exchange studies in ETSAM, Spain.
Research Experience
- Worked as an architect and consultant for both the private and public sector.
Education
- Postdoctoral Researcher (2023), ETH Zurich, DBAUG and DINFK, with Prof. Daniel Hall, Prof. Catherine de Wolf, and Prof. Marc Pollefeys; Ph.D. (2020), Civil and Environmental Engineering with Minor in Computer Science, Stanford University, with Prof. Martin Fischer and Prof. Silvio Savarese; MSc (2013), Computer Science, Ionian University; MEng (2011), Architectural Engineering, University of Tokyo; Diploma (2009), Architectural Engineering, National Technical University of Athens.
Background
- Focus on developing quantitative and data-driven methods that learn from real-world visual data to generate, predict, and simulate new or renewed built environments that place the human in the center. Goal is to create sustainable, inclusive, and adaptive built environments that can support our current and future physical and digital needs. Particularly interested in creating spaces that blend from 100% physical (real reality) to 100% digital (virtual reality) with the use of Mixed Reality.
Miscellany
- Currently teaching at Stanford: Designing for Gradient Spaces — CEE342, Spring; Computer Vision for the Built Environment — CEE 247C, Winter; AI Applications in AEC — CEE 329, Spring.
Co-authors