Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Weishan Bai

Biographic Data

ID3635887
NAMEWeishan Bai
GIVEN NAMESWeishan
FAMILY NAMEBai
SIGNATUREBAI W
AFFILIATIONSUrban Institute
ORCID0009-0000-2006-4456
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS4
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2024
LATEST PUBLICATION YEAR2025
H-INDEX2
  • Greener the safer? Effects of urban green space on community safety and perception of safety using satellite and street view imagery data

    Open Access•Qian He, Ling Wu et al.•ARTICLE•Journal of Criminal Justice•2025•Cited by: 2•References: 9

  • Reducing AI Model Biases with a Bilevel Learning Framework

    Weishan Bai, Xinyue Ye et al.•ARTICLE•Annals of the American…•2025•References: 52

    This study aims to improve disaster risk mitigation by integrating fairness into artificial intelligence (AI) models, specifically addressing spatial biases that can lead to unequal resource allocation during disasters. Our objective is to reduce spatial biases in disaster impact prediction models via a bilevel learning framework, enhancing both accuracy and fairness. To achieve this, we leverage information exchanges in social networks during th…

  • Enhancing population data granularity

    Open Access•Xinyue Ye, Weishan Bai et al.•ARTICLE•Cities•2024•Cited by: 2•References: 39

  • Greener the safer? Effects of urban green space on community safety and perception of safety using satellite and street view imagery data

    Open Access•Qian He, Ling Wu et al.•ARTICLE•Journal of Criminal Justice•2025•Cited by: 2•References: 9

  • Enhancing population data granularity

    Open Access•Xinyue Ye, Weishan Bai et al.•ARTICLE•Cities•2024•Cited by: 2•References: 39

  • Enhancing population data granularity

    Open Access•Xinyue Ye, Weishan Bai et al.•ARTICLE•Cities•2024•Cited by: 2•References: 39

  • Greener the safer? Effects of urban green space on community safety and perception of safety using satellite and street view imagery data

    Open Access•Qian He, Ling Wu et al.•ARTICLE•Journal of Criminal Justice•2025•Cited by: 2•References: 9

  • Reducing AI Model Biases with a Bilevel Learning Framework

    Weishan Bai, Xinyue Ye et al.•ARTICLE•Annals of the American…•2025•References: 52

    This study aims to improve disaster risk mitigation by integrating fairness into artificial intelligence (AI) models, specifically addressing spatial biases that can lead to unequal resource allocation during disasters. Our objective is to reduce spatial biases in disaster impact prediction models via a bilevel learning framework, enhancing both accuracy and fairness. To achieve this, we leverage information exchanges in social networks during th…

Computer Science (3 works) · Data science (2 works) · Impact of Light on Environment and Health (2 works) · Anomaly Detection Techniques and Applications (1 works) · Artificial Intelligence (1 works) · Computer security (1 works) · Data mining (1 works) · Data-Driven Disease Surveillance (1 works) · Demography (1 works) · Demography (1 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae