Draft:Iro Armeni
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| Submission declined on 24 December 2024 by KylieTastic (talk). This submission's references do not show that the subject qualifies for a Wikipedia article—that is, they do not show significant coverage (not just passing mentions) about the subject in published, reliable, secondary sources that are independent of the subject (see the guidelines on the notability of people). Before any resubmission, additional references meeting these criteria should be added (see technical help and learn about mistakes to avoid when addressing this issue). If no additional references exist, the subject is not suitable for Wikipedia. This submission is not adequately supported by reliable sources. Reliable sources are required so that information can be verified. If you need help with referencing, please see Referencing for beginners and Citing sources. Declined by KylieTastic 13 days ago. | |
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 | |
|---|---|
| Nationality | Greek |
| Alma mater | Stanford University (PhD) |
| Scientific career | |
| Fields | Civil and Environmental Engineering |
| Institutions | Stanford University |
| Doctoral advisor | Silvio Savarese Martin Fischer |
| Website | gradientspaces.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
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]
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 [4]. This innovation led to the creation of the first large-scale dataset of 3D indoor spaces (S3DIS). This dataset is now widely used [5] in the field of computer vision for training and benchmarking deep learning algorithms (such as PointNet[6]) for 3D semantic segmentation of large-scale indoor spaces.
Awards (Selection)
- 2017: Google PhD Fellowship in Machine Perception[7]
- 2020: ETH Zurich Postdoctoral Fellowship[8]
- 2014: EU Marie-Curie Fellowship (Automated As-Built Modelling of the Built Infrastructure)
- 2013: EU Marie-Curie Fellowship (BIMAutoGen)
- 2009: Monbukagakusho Scholarship (For Graduate Studies in Japan)
References
- ^ "Iro Armeni's Profile | Stanford Profiles". profiles.stanford.edu.
- ^ "Stanford researchers automate process for acquiring detailed building information". Stanford Report. June 29, 2016.
- ^ "Women in Computer Vision". Computer Vision News. September 5, 2018.
- ^ "Stanford Innovation Makes Point Clouds Smart". geoweeknews.com. July 20, 2016.
- ^ "Stanford 3D Indoor Scene Dataset (S3DIS)". PapersWithCode.
- ^ "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation". PointNet.
- ^ "CEE PhD student Iro Armeni awarded Google PhD Fellowship | Civil and Environmental Engineering". cee.stanford.edu. April 11, 2017.
- ^ "List of ETH Fellows". Grants Office.
External links
- Iro Armeni's Home Page
- Iro Armeni at DBLP Bibliography Server
- Iro Armeni's publications indexed by Google Scholar