Hasan Ahamed Alif

About

Hasan Ahamed Alif is a Computer Science and Engineering graduate from Anna University, Chennai, India, with research interests at the intersection of artificial intelligence, machine learning, geospatial data science, remote sensing, and Earth system science. His work focuses on developing interpretable and data-driven solutions for climate forecasting, flood risk assessment, urban heat island analysis, renewable energy forecasting, and sustainable infrastructure planning.

His research integrates advanced machine learning, deep learning, GIS, and satellite remote sensing to address real-world environmental and societal challenges. He has authored multiple peer-reviewed journal and conference publications in leading international venues, including Springer Nature and IEEE, covering topics such as climate anomaly detection, rainfall prediction, temperature forecasting, explainable AI, and spatial environmental modeling.

Beyond his research contributions, Hasan actively serves the scientific community as a reviewer and technical program committee member for several international journals and IEEE conferences. His technical expertise includes Python, TensorFlow, Scikit-learn, GIS, remote sensing, ensemble learning, time-series forecasting, and explainable artificial intelligence.

His long-term research vision is to advance trustworthy and interpretable AI for climate resilience, environmental sustainability, disaster risk reduction, and intelligent decision-support systems that contribute to achieving the United Nations Sustainable Development Goals (SDGs).

Employment

• Dhaanish Ahmed college of Engineering Student
  2022 - 2026

Education

• Anna University, Chennai B.E.
  2022 - 2026

Projects & Funding

Projects & funding information is unavailable.

Publications (22)

• Risk-informed flood management under climate variability: A hybrid temporal–ensemble artificial intelligence framework
  Bulletin of Atmospheric Science and Technology 2026 DOI: 10.1007/s42865-026-00126-4
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• Artificial Intelligence-Driven Rainfall Forecasting and GIS-Based Flood Risk Mapping for Climate-Resilient Infrastructure in Bangladesh
  Earth Systems and Environment 2026 DOI: 10.1007/s41748-025-00958-8
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• Unsupervised Machine Learning for Climate Surveillance: Comparative Temperature Anomaly Detection in Northwestern Bangladesh
  2025 2nd International Conference on Integration of Computational Intelligent System (ICICIS) 2026 DOI: 10.1109/icicis65613.2025.11371242
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• Machine learning-driven rainfall forecasting model for sustainable and adaptive infrastructure planning
  Discover Sustainability 2026 DOI: 10.1007/s43621-026-02699-8
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• Causality-Informed XGBoost Framework for Attribution of Temperature Extremes in Remote Maritime Climates using Climate Oscillation Patterns in Australia
  2025 5th International Conference on Mobile Networks and Wireless Communications (ICMNWC) 2026 DOI: 10.1109/icmnwc66779.2025.11354315
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• Adaptive Ensemble Learning with Dynamic Weighting for Regional Temperature Extremes Detection Using Climate Teleconnections in Australia
  2025 10th International Conference on Communication and Electronics Systems (ICCES) 2026 DOI: 10.1109/icces67310.2025.11337026
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• Integrated Hybrid AI–GIS Framework for Temperature-Driven Drought Early Warning and Agricultural Risk Mapping in Bangladesh
  2026 DOI: 10.31223/X5HF3P
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• Agricultural impact on groundwater utilization in the Manimuktha sub-basin of Vellar River
  Environmental Earth Sciences 2026 DOI: 10.1007/s12665-025-12725-z
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• Development of robust statistical and machine learning ensemble models for long-term temperature forecasting in central Ethiopia
  Bulletin of Atmospheric Science and Technology 2026 DOI: 10.1007/s42865-025-00118-w
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• Volumetric MRI-Based Lesion Segmentation in Traumatic Brain Injury via a 3D U-Net Deep Learning Model
  Proceedings of the 9th International Conference on Inventive Systems and Control Icisc 2025 2025 DOI: 10.1109/ICISC65841.2025.11187483
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