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{{Short description|Greek-American civil engineer}}
{{Short description|Greek-American civil engineer}}
{{Draft topics|biography|stem}}
{{AfC topic|blp}}
{{AfC submission|||ts=20241225050647|u=Purrfectcharlie|ns=118}}
{{AFC submission|d|bio|u=Purrfectcharlie|ns=118|decliner=Johannes Maximilian|declinets=20241225005650|ts=20241224194315}} <!-- Do not remove this line! -->
{{AFC submission|d|bio|u=Purrfectcharlie|ns=118|decliner=KylieTastic|declinets=20241224184344|reason2=v|small=yes|ts=20241224184245}} <!-- Do not remove this line! -->

{{AFC comment|1=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, --[[User:Johannes Maximilian|Johannes]] ([[User_Talk:Johannes Maximilian|Talk]]) <small>([[Special:Contribs/Johannes Maximilian|Contribs]]) ([[User:Johannes Maximilian/Articles2|Articles]])</small> 00:56, 25 December 2024 (UTC)}}

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{{Infobox scientist
{{Infobox scientist
| name = Iro Armeni
| name = Iro Armeni
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| work_institution = [[Stanford University]]
| work_institution = [[Stanford University]]
| alma_mater = [[Stanford University]] (PhD)
| alma_mater = [[Stanford University]] (PhD)
| doctoral_advisor = [[Silvio Savarese]]
| doctoral_advisor = [[Silvio Savarese]] [[Martin Fischer]]
| website = [https://gradientspaces.stanford.edu gradientspaces.stanford.edu]
| website = [https://gradientspaces.stanford.edu gradientspaces.stanford.edu]
| doctoral_students =
| doctoral_students =
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}}
}}


'''Iro Armeni''' ({{langx|el|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.
'''Iro Armeni''' ({{langx|el|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.<ref>{{Cite web|url=https://profiles.stanford.edu/iro-armeni|title=Iro Armeni's Profile &#124; Stanford Profiles|website=profiles.stanford.edu}}</ref>

==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<ref>{{Cite news|url=https://news.stanford.edu/stories/2016/06/stanford-researchers-automate-process-acquiring-detailed-building-information|title=Stanford researchers automate process for acquiring detailed building information|date=June 29, 2016|website=Stanford Report}}</ref>,
emphasizing the spatiotemporal understanding of buildings, from the moment they get constructed to the moment they get demolished.<ref>{{Cite news|url=https://www.rsipvision.com/ComputerVisionNews-2018September/24/|title=Women in Computer Vision|date=September 5, 2018|website=Computer Vision News}}</ref> Her research contributes to enhancing the [[sustainability]] of [[construction]] and the build environment through the use of [[artificial intelligence]].<ref>{{cite book |last= |first= |author-link= |date= 2024|title=A Circular Built Environment in the Digital Age (Circular Economy and Sustainability) |url=https://link.springer.com/book/10.1007/978-3-031-39675-5 |location= |publisher=Springer |page=57 |doi= 10.1007/978-3-031-39675-5|isbn=978-3031396748
}}</ref>

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 <ref>{{Cite news|url=https://www.geoweeknews.com/news/stanford-innovation-makes-point-clouds-smart|title=Stanford Innovation Makes Point Clouds Smart|date=July 20, 2016|website=geoweeknews.com}}</ref>.
This innovation led to the creation of the first large-scale dataset of 3D indoor spaces ([https://redivis.com/datasets/9q3m-9w5pa1a2h S3DIS]).
This dataset is now widely used
<ref>{{cite web|url=https://paperswithcode.com/dataset/s3dis|title=Stanford 3D Indoor Scene Dataset (S3DIS)|website=PapersWithCode}}</ref> in the field of [[computer vision]] for training and benchmarking [[deep learning]] algorithms (such as PointNet<ref>{{cite web|url=https://stanford.edu/~rqi/pointnet/|title=PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation|website=PointNet}}</ref>) for 3D semantic segmentation of large-scale indoor spaces.

==Awards (Selection)==
* 2017: [[Google]] PhD Fellowship in Machine Perception<ref>{{Cite web|url=https://cee.stanford.edu/news/cee-phd-student-iro-armeni-awarded-google-phd-fellowship|title=CEE PhD student Iro Armeni awarded Google PhD Fellowship &#124; Civil and Environmental Engineering|date=April 11, 2017|website=cee.stanford.edu}}</ref>
* 2020: [[ETH Zurich]] Postdoctoral Fellowship<ref>{{Cite web|url=https://grantsoffice.ethz.ch/funding-opportunities/internal/eth-fellowships/list-of-fellows.html|title=List of ETH Fellows|website=Grants Office}}</ref>
* 2014: [https://en.wikipedia.org/wiki/Marie_Sk%C5%82odowska-Curie_Actions EU Marie-Curie Fellowship] (Automated As-Built Modelling of the Built Infrastructure)
* 2013: [https://en.wikipedia.org/wiki/Marie_Sk%C5%82odowska-Curie_Actions EU Marie-Curie Fellowship] (BIMAutoGen)
* 2009: [[Monbukagakusho Scholarship]] (For Graduate Studies in Japan)

== References ==
{{Reflist}}

== External links ==
*[https://ir0.github.io/ Iro Armeni's Home Page]
*[https://dblp.org/pid/132/5216.html Iro Armeni] at [[DBLP]] Bibliography Server
*[https://scholar.google.com/citations?user=m2oTZkIAAAAJ&hl=en&oi=ao Iro Armeni's publications] indexed by [[Google Scholar]]

Latest revision as of 05:31, 25 December 2024

  • 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

[edit]

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)

[edit]

References

[edit]
  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.
[edit]
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