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Draft:Iro Armeni

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  • Comment: On English Wikipedia, assistant professors are not inherently notable, i.e., you must demonstrate what makes the subject notable by citing reliable, secondary, and intellectually independent sources that discuss the subject in significant detail. Best, --Johannes (Talk) (Contribs) (Articles) 00:56, 25 December 2024 (UTC)


Iro Armeni
NationalityGreek
Alma materStanford University (PhD)
Scientific career
FieldsCivil and Environmental Engineering
InstitutionsStanford University
Doctoral advisorSilvio Savarese Martin Fischer
Websitegradientspaces.stanford.edu

Iro Armeni (Greek: Ιρό Αρμένη) is an Assistant Professor of Civil and Environmental Engineering at Stanford University. She heads the Gradient Spaces Research group in the Civil and Environmental Engineering Department.[1]

Research

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Armeni's research lies at the intersection of computer vision, civil engineering and architecture. Her work focuses on the semantic parsing of buildings and their affordances[2], emphasizing the spatiotemporal understanding of buildings, from the moment they get constructed to the moment they get demolished.[3] Her research contributes to enhancing the sustainability of construction and the build environment through the use of artificial intelligence.[4]

One of Armeni's most notable contributions is the development of a computer-vision algorithm that automates the semantic segmentation of point clouds representing large-scale 3D indoor spaces [5]. This innovation led to the creation of the first large-scale dataset of 3D indoor spaces (S3DIS). This dataset is now widely used [6] in the field of computer vision for training and benchmarking deep learning algorithms (such as PointNet[7]) for 3D semantic segmentation of large-scale indoor spaces.

Awards (Selection)

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References

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  1. ^ "Iro Armeni's Profile | Stanford Profiles". profiles.stanford.edu.
  2. ^ "Stanford researchers automate process for acquiring detailed building information". Stanford Report. June 29, 2016.
  3. ^ "Women in Computer Vision". Computer Vision News. September 5, 2018.
  4. ^ A Circular Built Environment in the Digital Age (Circular Economy and Sustainability). Springer. 2024. p. 57. doi:10.1007/978-3-031-39675-5. ISBN 978-3031396748.
  5. ^ "Stanford Innovation Makes Point Clouds Smart". geoweeknews.com. July 20, 2016.
  6. ^ "Stanford 3D Indoor Scene Dataset (S3DIS)". PapersWithCode.
  7. ^ "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation". PointNet.
  8. ^ "CEE PhD student Iro Armeni awarded Google PhD Fellowship | Civil and Environmental Engineering". cee.stanford.edu. April 11, 2017.
  9. ^ "List of ETH Fellows". Grants Office.
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