He/Him/His
Focus Area: Geospatial Analysis and Techniques
Country of Origin: Bangladesh
Degree Program: PhD
Entered Program: Spring 2024
Expected Graduation: Summer 2027
Dissertation Topic: TBD
Research Statement: I am actively engaged in geospatial data science, remote sensing, and artificial intelligence, with a strong focus on environmental modeling, sustainability, and land-use dynamics. My research integrates machine learning, deep learning, and GIS-based modeling to analyze, predict, and mitigate environmental changes that impact ecosystems and human settlements. At the core of my work is the goal of building models that effectively capture human-environment interactions, enabling data-driven solutions for sustainable development and resilience planning.
My research has encompassed spatiotemporal analysis of land cover changes, predictive modeling of environmental processes. I have utilized segmentation models for remote sensing data, improving land cover classification, feature extraction, and object-based analysis for high-resolution environmental monitoring. Additionally, I have applied foundational geospatial AI models for land-use classification and sustainability assessments, particularly in agricultural and ecological systems.
Currently, I am working on developing generative models for remote sensing data, aiming to enhance data augmentation, improve spatial resolution, and fill critical gaps in Earth observation datasets. By creating frameworks that link anthropogenic activities, environmental stressors, and sustainability indicators, I aim to provide data-driven insights for policy decisions, conservation strategies, and urban resilience planning. Through my expertise in Remote Sensing, Generative AI, and novel model architectures, I continue to explore innovative solutions to better understand how human actions shape—and are shaped by—the environment.
Adviser: Dr. Jane Southworth
Educational Background
- M.S. In Geography University of Florida, 2023
- B.S. in Urban and regional Planning, Khulna University of Engineering &Technology, 2020
Recent publications
Rahaman, M., Southworth, J., Amanambu, A. C., Tefera, B. B., Alruzuq, A. R., Safaei, M., … & Smith, A. C. (2025). Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data. Journal of Environmental Management, 376, 124323.
Southworth, J., Smith, A. C., Safaei, M., Rahaman, M., Alruzuq, A., Tefera, B. B., … & Herrero, H. V. (2024). Machine learning versus deep learning in land system science: a decision-making framework for effective land classification. Frontiers in Remote Sensing, 5, 1374862.