Role: 

As the Lead Author and Primary Investigator, I

1. Spearheaded the research project from beginning to submission

2. Providing strategic leadership and team coordination.

3. Established the theoretical foundation through a comprehensive literature review and conceptual development.

4. Designing and conducting the foundational field survey

5. Managing technical processes, including data curation, formal analysis, validation, and visualization software implementation.

6. Writing the original manuscript draft and managing the rigorous review and editing process.

Key Outcomes:

1. Present a comprehensive quantitative assessment of the key factors and sub-factors driving flood hazard, vulnerability, and integrated risk.

2. Three separate maps of hazard, vulnerability, and risk delineating five different levels of intensity across the study area to help institutions identify urgent-risk zones.

3. Precise spatial distribution and extent for each criterion and sub-criterion within each FRZ, revealed through a Comprehensive Geospatial Analysis.

4. Qualitative Comparative Analysis identified functionally viable NBS for each FRZ and visualized the findings with maps.

5. Generated a flood inventory map with historical flooded and non-flooded points through stakeholder surveys and literature review, and achieved an accuracy of 91.30% ROC-AUC.

 Skill Gained:

1. Quantitative Risk & Geospatial Analysis

2. Spatial MCDA (AHP/FAHP) & Flood Inventory Mapping

3. Statistical Programming in Python (ROC, Sensitivity Analysis)

4. Field Survey Design & Qualitative Comparative Analysis

Role: 

As a 2nd Author and Primary Investigator, I

1. Conducting the literature review, identifying the research gap, and designing the methodological framework.

2. Coordinating the team and managing task distribution.

3. Performing data analysis, validation, and visualization;

4. drafting the Abstract, Introduction, and Results; and leading manuscript review and editing.

Key Outcomes:

1. Suitability Mapping: 84.21% of the Barguna District's land was classified as suitable for cyclone shelter construction, with only 15.8% deemed high-risk or unsuitable.

2. Critical Factors: The AHP confirmed that the most critical factors for shelter suitability are Proximity to Hospital (27.1%), Population Density (24.2%), and Proximity to Road (18.4%).

3. Targeted Intervention Zones: Hotspot/Cold Spot analysis successfully delineated specific spatial clusters: Cold Spots identifying ideal, safe locations, and Hot Spots marking high-risk, unsuitable zones.

4. Policy Framework: The study developed a replicable and data-driven framework for policymakers to prioritize the construction of new shelters and mitigate socio-political influences on shelter placement.

Skill Gained:

1. Geospatial Analysis: Executing spatial modeling in ArcGIS using AHP and Weighted Overlay for suitability mapping.

2. Spatial Statistics: Applying Getis-Ord Gi* for hotspot analysis to map significant socio-environmental clusters.

3. Field Research: Managing end-to-end primary data collection, validation, and analysis.

Abstract

Increasingly frequent and severe compound flooding under climate change demands solutions beyond traditional engineering. This study develops a GIS-based framework to identify optimal sites for small-scale Nature-based Solutions (NBS) to mitigate flood vulnerability in Chittagong, Bangladesh. Employing a Spatial Multi-Criteria Analysis (SMCA) framework weighted via the Analytical Hierarchy Process (AHP), we integrated five key geophysical factors: elevation, distance to rivers, slope, land use/land cover, and soil texture. The resulting vulnerability map classifies the area as highly vulnerable (21%; 895.2 km²), vulnerable (42%; 1830 km²), less vulnerable (28%; 1224.6 km²), and not vulnerable (9%; 383 km²). The model demonstrated good predictive accuracy (ROC-AUC = 0.781). Building on this, Qualitative Comparative Analysis (QCA) identified priority sites for specific NBS by mapping areas where high vulnerability coincides with geophysical suitability for implementation.

Abstract

This study aims to analyse the characteristics of the back material used in Organization Z’s smartphones compared to those of other market competitors, following customer requirements. It also seeks to identify the most suitable material to increase customer satisfaction. Using the main tool of Quality Function Deployment (QFD), the House of Quality (HOQ), absolute and relative weight values were identified. These values were based on customer requirements, which were obtained from a customer survey, and on technical descriptors. These values guided the selection of an optimal material. Among the materials studied, alkali-aluminosilicate sheet glass emerged as the most suitable, exhibiting the highest absolute and relative weights. This chosen material, alkali-aluminosilicate sheet glass, was expected to meet customer demands most effectively. Overall, the study yielded valuable insights for decision-making and improving customer satisfaction in Organization Z’s smartphone offerings.

As climate change intensifies worldwide, with floods posing significant challenges for water managers, traditional measures have proven inadequate. Ali et al. (2017) reveal Bangladesh's largely dependency on conventional 'grey' infrastructure such as dykes, embankments, polders, levees, bunds, floodwalls, concrete drainages, and shelter construction along with flood forecasting, early warning system. Moreover, Rammelt et al. (2018) underscored the controversy and failure of structural flood management projects in Bangladesh. Therefore, employing more adaptive measures, such as NBS, to tackle flood challenges is now becoming the preferred approach, given rapid urbanization and climate change. Chowdhooree et al. (2023) also illustrate Bangladesh's leading opportunity in showing how high-quality NBS deployment is in low- to middle-income countries. Therefore, this study aims to allocate NBS measures in an exposed coastal district of Chittagong to mitigate flood risk using a Spatial Multi-Criteria Analysis (SMCA) approach, the Analytical Hierarchy Process (AHP), and Geographic Information Systems (GIS). The allocation process analyzes the relative importance of several factors, such as elevation, slope, distance to rivers, land use and land cover (LULC), and soil texture, in determining and ranking vulnerable areas for the allocation of NBS measures.

This study aims to analyse the characteristics of the back material used in Organization Z's smartphones compared to those of other market competitors, following customer requirements. It also seeks to identify the most suitable material to increase customer satisfaction. Using the main tool of Quality Function Deployment (QFD), the House of Quality (HOQ), absolute and relative weight values were identified. These values were based on customer requirements, which were obtained from a customer survey, and on technical descriptors. These values guided the selection of an optimal material. Among the materials studied, alkali-aluminosilicate sheet glass emerged as the most suitable, exhibiting the highest absolute and relative weights. This chosen material, alkali aluminosilicate sheet glass, was expected to meet customer demands most effectively. Overall, the study yielded valuable insights for decision-making and improving customer satisfaction in Organization Z's smartphone offerings.

This study examines pandemic-related disruptions in Bangladesh's ready-made garment industry, ranking key challenges such as unpredictable demand, supply and labor disturbances, and financial and operational difficulties. Using expert opinions and analytical methods, including Interpretive Structural Modeling, the research identifies and maps these barriers. It provides a clear hierarchical framework to help decision-makers understand and prioritize the organizational changes needed to build resilient supply chains during global crises, offering practical guidance for the industry in developing nations.