Yingjing Huang

Postdoc @ University of Vienna

Hi, I am Yingjing Huang (黄颖菁). 👋 I am a University Assistant Postdoc at the Department of Geography and Regional Research, University of Vienna, where I work with Prof. Krzysztof Janowicz.

My research lies at the intersection of GIScience, GeoAI, and computer vision. I develop methods that use street-level and satellite imagery to measure and understand urban environments at scale. More broadly, I am interested in how spatial representations, foundation models, and multimodal AI can support reliable, interpretable, and geographically grounded analyses of cities.

My current work spans urban visual intelligence, spatial representation learning, GeoAI reproducibility, and the evaluation of geographic alignment in AI systems. Across these topics, I am particularly interested in connecting advances in machine learning with meaningful geographic questions and socially relevant urban applications.

Before joining the University of Vienna, I received my Ph.D. in Geographic Information Science from Peking University, advised by Prof. Lun Wu (邬伦), Prof. Yu Liu (刘瑜), and Prof. Fan Zhang (张帆). During my doctoral studies, I spent a year as a visiting researcher at the MIT Senseable City Lab. I previously received my B.S. and M.S. degrees from Wuhan University under the supervision of Prof. Teng Fei (费腾).

news

Sep 18, 2026	🎉 Our paper “How Geographic Information Influences Vision-Language Model Judgments of Urban Scenes” has been accepted as a full research paper to the 9th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI ‘26)!
Aug 05, 2026	🎉 Two papers accepted to ACM SIGSPATIAL 2026
Jul 16, 2026	📄 Our perspective article on “Advancing urban sustainability with visual intelligence” is accepted to Science Bulletin 🎉🎉
Apr 26, 2026	📢 Call for Papers: Special Issue on GeoAI for Urban Sustainability (TUS)
Apr 25, 2026	⏰ Deadline Extended: Geography According to Foundation Models @ AGILE 2026

selected publications

CEUS

Learning street view representations based on a spatiotemporal contrastive learning framework

Yong Li, Yingjing Huang, and Fan Zhang

Computers, Environment and Urban Systems, 2026

DOI Bib PDF

@article{li2026learning,
  title = {Learning street view representations based on a spatiotemporal contrastive learning framework},
  author = {Li, Yong and Huang, Yingjing and Zhang, Fan},
  year = {2026},
  journal = {Computers, Environment and Urban Systems},
  volume = {125},
  pages = {102393},
  issn = {0198-9715},
  language = {en},
  doi = {10.1016/j.compenvurbsys.2025.102393},
  co_first = {true},
}

Cities

Measuring urban physical environments using image deep features

Yingjing Huang, Fan Zhang, Lun Wu, and Yu Liu

Cities, 2025

DOI Bib PDF Code

@article{huang2025measuringa,
  title = {Measuring urban physical environments using image deep features},
  author = {Huang, Yingjing and Zhang, Fan and Wu, Lun and Liu, Yu},
  year = {2025},
  journal = {Cities},
  volume = {166},
  pages = {106196},
  issn = {0264-2751},
  language = {en},
  doi = {10.1016/j.cities.2025.106196},
}

GSIS WHU

Intelligent Computational Representation of Urban Imagery

Yingjing Huang, Fan Zhang, Yong Li, Lun Wu, and Yu Liu

Geomatics and Information Science of Wuhan University, 2025

(in Chinese)

DOI Bib PDF

@article{huang2025cheng,
  title = {Intelligent Computational Representation of Urban Imagery},
  author = {Huang, Yingjing and Zhang, Fan and Li, Yong and Wu, Lun and Liu, Yu},
  year = {2025},
  journal = {Geomatics and Information Science of Wuhan University},
  volume = {0},
  number = {0},
  issn = {1671-8860},
  language = {cn},
  doi = {10.13203/j.whugis20240472},
}

B&E

No “true” greenery: Deciphering the bias of satellite and street view imagery in urban greenery measurement

Yingjing Huang, Rohit Priyadarshi Sanatani, Chang Liu, Yuhao Kang, Fan Zhang, Yu Liu, Fabio Duarte, and Carlo Ratti

Building and Environment, 2025

DOI Bib PDF Code Website

@article{huang2025no,
  title = {No ``true'' greenery: Deciphering the bias of satellite and street view imagery in urban greenery measurement},
  author = {Huang, Yingjing and Sanatani, Rohit Priyadarshi and Liu, Chang and Kang, Yuhao and Zhang, Fan and Liu, Yu and Duarte, Fabio and Ratti, Carlo},
  year = {2025},
  journal = {Building and Environment},
  volume = {269},
  pages = {112395},
  issn = {03601323},
  doi = {10.1016/j.buildenv.2024.112395},
  language = {en},
}

CEUS

Comprehensive Urban Space Representation with Varying Numbers of Street-Level Images

Yingjing Huang, Fan Zhang, Yong Gao, Wei Tu, Fabio Duarte, Carlo Ratti, Diansheng Guo, and Yu Liu

Computers, Environment and Urban Systems, Dec 2023

DOI Bib PDF Code Website

@article{huang2023comprehensive,
  title = {Comprehensive Urban Space Representation with Varying Numbers of Street-Level Images},
  author = {Huang, Yingjing and Zhang, Fan and Gao, Yong and Tu, Wei and Duarte, Fabio and Ratti, Carlo and Guo, Diansheng and Liu, Yu},
  year = {2023},
  month = dec,
  journal = {Computers, Environment and Urban Systems},
  volume = {106},
  pages = {102043},
  issn = {0198-9715},
  language = {en},
  doi = {10.1016/j.compenvurbsys.2023.102043},
  urldate = {2023-10-12},
}