Yingjing Huang

Remote sening building, Peking University

No.5 Yiheyuan Road

Beijing, China 100871

Hey, I am Yingjing Huang (黄颖菁). 👋

I am a Ph.D. candidate in Cartograpghy and Geographic Information Science at Peking University, China, under the joint supervision of Prof. Lun Wu (邬伦), Prof. Yu Liu (刘瑜), and Prof. Fan Zhang (张帆). Previously, I was a visiting Ph.D. student at the MIT Senseable City Lab for one year. I hold a bachelor’s and master’s degree from Wuhan University, China, and my advisor was Prof. Teng Fei (费腾).

My research intersects GIScience and Computer Vision, with a focus on urban visual AI and its implications for guiding urban planning.

Currently, I am working on my doctoral thesis, which focuses on using GeoAI to represent the urban physical environment based on urban imagery, primarily involving remote sensing imagery and street-level imagery. We want to understand how humans transform urban physical spaces and how these spaces, in turn, reflect human daily life.

With my doctoral degree expected in June 2025, I am currently seeking faculty or postdoctoral positions.

news

Apr 16, 2025	Our paper on “Intelligent Computational Representation of Urban Imagery” （in Chinese）is accepted to Geomatics and Information Science of Wuhan University 🎉🎉
Dec 01, 2024	Our paper on “No “true” greenery: Deciphering the bias of satellite and street view imagery in urban greenery measurement” is accepted to Building and Environment 🎉🎉
Apr 17, 2024	Presentation on 2024 AAG Annual Meeting
Sep 23, 2023	Our paper on “Comprehensive urban space representation with varying numbers of street-level images” is accepted to Computers, Environment and Urban Systems 🎉🎉
Jan 06, 2023	I am starting my visit at the MIT Senseable City Lab as a visiting Ph.D. student.

selected publications

Intelligent Computational Representation of Urban Imagery

Yingjing Huang, Fan Zhang, Yong Li, and 2 more authors

Geomatics and Information Science of Wuhan University, 2025

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},
  doi = {10.13203/j.whugis20240472},
}

No-True-Greenery

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

Yingjing Huang, Rohit Priyadarshi Sanatani, Chang Liu, and 5 more authors

Building and Environment, 2025

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},
  language = {en},
}

Vision-LSTM

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

Yingjing Huang, Fan Zhang, Yong Gao, and 5 more authors

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},
  doi = {10.1016/j.compenvurbsys.2023.102043},
  urldate = {2023-10-12},
}

GIS-Based Emotional Computing: A Review of Quantitative Approaches to Measure the Emotion Layer of Human–Environment Relationships

Yingjing Huang, Teng Fei, Mei-Po Kwan, and 5 more authors

ISPRS International Journal of Geo-Information, Sep 2020

DOI Bib PDF

@article{Huang2020gis,
  title = {{{GIS-Based Emotional Computing}}: {{A Review}} of {{Quantitative Approaches}} to {{Measure}} the {{Emotion Layer}} of {{Human}}--{{Environment Relationships}}},
  shorttitle = {{{GIS-Based Emotional Computing}}},
  author = {Huang, Yingjing and Fei, Teng and Kwan, Mei-Po and Kang, Yuhao and Li, Jun and Li, Yizhuo and Li, Xiang and Bian, Meng},
  year = {2020},
  month = sep,
  journal = {ISPRS International Journal of Geo-Information},
  volume = {9},
  number = {9},
  pages = {551},
  issn = {2220-9964},
  doi = {10.3390/ijgi9090551},
  urldate = {2022-04-09},
  langid = {english},
}

Bias-in-Place-Emotion

Quantifying the Bias in Place Emotion Extracted from Photos on Social Networking Sites: A Case Study on a University Campus

Yingjing Huang, Jun Li, Guofeng Wu, and 1 more author

Cities, Jul 2020

DOI Bib PDF

@article{Huang2020quantifying,
  title = {Quantifying the Bias in Place Emotion Extracted from Photos on Social Networking Sites: {{A}} Case Study on a University Campus},
  shorttitle = {Quantifying the Bias in Place Emotion Extracted from Photos on Social Networking Sites},
  author = {Huang, Yingjing and Li, Jun and Wu, Guofeng and Fei, Teng},
  year = {2020},
  month = jul,
  journal = {Cities},
  volume = {102},
  pages = {102719},
  issn = {02642751},
  doi = {10.1016/j.cities.2020.102719},
  urldate = {2022-04-09},
}