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Maryam Hosseini

Biographic Data

ID4094566
NAMEMaryam Hosseini
GIVEN NAMESMaryam
FAMILY NAMEHosseini
SIGNATUREHOSSEINI M
AFFILIATIONSMassachusetts Institute of Technology
ORCID0000-0002-7482-6185
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS0
AUTHOR COUNT5
EDITOR COUNT0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2025
H-INDEX0
  • A sidewalk-level urban heat risk assessment framework using pedestrian mobility and urban microclimate modeling

    Open Access•Nicola Colaninno, Rounaq Basu et al.•ARTICLE•Environment and Planning B Urban…•2025

    Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and r…

  • Effectiveness of a school-based oral health literacy promotion intervention

    Open Access•Maryam Hosseini, Maryam Sadat Hosseini et al.•ARTICLE•BMC Public Health•2025

    The study confirmed that a school-based educational intervention significantly improved oral health literacy (OHL) among female students. Significant increases were observed across all OHL domains in the experimental group, highlighting the effectiveness of structured interventions in promoting oral health awareness and behaviors among adolescents. While the study confirmed the intervention's effectiveness, it was limited to female students; futu…

  • Contextualized poverty targeting with multimodal spatial data and machine learning in Brazzaville, Congo

    Open Access•Woo-Jin Jung, WooJin Jung et al.•ARTICLE•Cities•2025•References: 2

    Enhancing targeting accuracy in social welfare programs fosters equitable urban development. Advancements in this field harness georeferenced data and leverage AI/machine learning (ML) techniques to predict poverty and allocate aid. However, these models are predominantly developed in areas with georeferenced national surveys and are intended for geographic targeting. We demonstrate that household-level targeting can be achieved in understudied c…

  • Mapping the walk

    Open Access•Maryam Hosseini, Andres Sevtsuk et al.•ARTICLE•Computers Environment and Urban…•2023

  • CitySurfaces

    Open Access•Maryam Hosseini, Fabio Miranda et al.•ARTICLE•Sustainable Cities and Society•2022

No prominent works on this page.

  • CitySurfaces

    Open Access•Maryam Hosseini, Fabio Miranda et al.•ARTICLE•Sustainable Cities and Society•2022

  • Mapping the walk

    Open Access•Maryam Hosseini, Andres Sevtsuk et al.•ARTICLE•Computers Environment and Urban…•2023

  • A sidewalk-level urban heat risk assessment framework using pedestrian mobility and urban microclimate modeling

    Open Access•Nicola Colaninno, Rounaq Basu et al.•ARTICLE•Environment and Planning B Urban…•2025

    Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and r…

  • Effectiveness of a school-based oral health literacy promotion intervention

    Open Access•Maryam Hosseini, Maryam Sadat Hosseini et al.•ARTICLE•BMC Public Health•2025

    The study confirmed that a school-based educational intervention significantly improved oral health literacy (OHL) among female students. Significant increases were observed across all OHL domains in the experimental group, highlighting the effectiveness of structured interventions in promoting oral health awareness and behaviors among adolescents. While the study confirmed the intervention's effectiveness, it was limited to female students; futu…

  • Contextualized poverty targeting with multimodal spatial data and machine learning in Brazzaville, Congo

    Open Access•Woo-Jin Jung, WooJin Jung et al.•ARTICLE•Cities•2025•References: 2

    Enhancing targeting accuracy in social welfare programs fosters equitable urban development. Advancements in this field harness georeferenced data and leverage AI/machine learning (ML) techniques to predict poverty and allocate aid. However, these models are predominantly developed in areas with georeferenced national surveys and are intended for geographic targeting. We demonstrate that household-level targeting can be achieved in understudied c…

Engineering (3 works) · Geography (3 works) · Transport engineering (3 works) · Artificial Intelligence (2 works) · Cartography (2 works) · Civil engineering (2 works) · Computer Science (2 works) · Impact of Light on Environment and Health (2 works) · Pedestrian (2 works) · Segmentation (2 works)

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