Mahmud Afroz
Researcher
Graduate Student Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Mahmud Afroz's research has explored the application of remote sensing and machine learning techniques to address complex societal and environmental issues. His work includes a systematic review of urban flood susceptibility mapping, examining various modeling approaches that utilize remote sensing and machine learning. Afroz has also investigated landscape dynamics in peri-urban areas using remote sensing, with a case study in Bangladesh. In parallel, his research extends to public health, focusing on maternal healthcare service utilization and its determinants in Bangladesh, analyzing temporal trends from 2011 to 2022. Additionally, he has applied supervised machine learning to predict child development across multiple domains, utilizing data from a cross-sectional study in Bangladesh.
Metrics
- h-index: 1
- Publications: 1
- Citations: 57
Selected Publications
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Maternal Healthcare Service Utilization in Bangladesh: A Cross‐Sectional Study of Determinants and Temporal Trends Using BDHS 2011–2022 (2026)
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Deep Learning–Based Multivariate Time Series Forecasting of Acute Respiratory Infections Among Rohingya Refugees in Cox's Bazar, Bangladesh (2025)
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Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh (2025)
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A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches (2025)
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ASSESMENT OF ECONOMIC LOSS AND CASUALTIES DUE TO EARTHQUAKES OF DIFFERENT MAGNITUDES AT THE NEW MADRID FAULT ZONE (2022)
Collaboration Network
Top Collaborators
- Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh
- Maternal Healthcare Service Utilization in Bangladesh: A Cross‐Sectional Study of Determinants and Temporal Trends Using BDHS 2011–2022
- Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh
- Maternal Healthcare Service Utilization in Bangladesh: A Cross‐Sectional Study of Determinants and Temporal Trends Using BDHS 2011–2022
- A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches
- A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches
- A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches
- Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh
- Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh
- Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh
- Predicting Child Development Across Literacy, Physical, Learning, and Social‐Emotional Domains Using Supervised Machine Learning: A Cross‐Sectional Study Based on MICS 2019 Bangladesh
- Maternal Healthcare Service Utilization in Bangladesh: A Cross‐Sectional Study of Determinants and Temporal Trends Using BDHS 2011–2022
- Maternal Healthcare Service Utilization in Bangladesh: A Cross‐Sectional Study of Determinants and Temporal Trends Using BDHS 2011–2022
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