Mohammed Alokshiya is a multidisciplinary researcher and logistics professional with over a decade of experience bridging climate resilience, civil engineering, and humanitarian operations. He combines academic research on sustainability and 3D concrete printing at UNU and TU Dresden with frontline logistics roles at WFP and UNRWA, demonstrating rare expertise in both life cycle assessment and emergency fleet management in conflict-affected settings. Skilled in Python, QGIS, Stata and AutoCAD, he translates quantitative analysis into practical interventions—from carbon footprint studies to port rehabilitation and vehicle control systems. His background includes hands-on fieldwork, GIS analysis, and systematic reviews, plus an unexpected creative edge as an award-winning novelist fluent in Arabic and English. Based in the Netherlands, Mohammed excels at turning complex technical research into actionable policy and operational solutions for vulnerable communities.
10 years of coding experience
8 years of employment as a software developer
Master's degree Civil Engineering, Master's degree Civil Engineering at Islamic University of Gaza
Master's degree Urban Management and Development (Urban Environment Sustainability and Climate Change), Master's degree Urban Management and Development (Urban Environment Sustainability and Climate Change) at Erasmus University Rotterdam
Contributions:13 reviews, 8 commits, 12 PRs in 2 years 9 months
Contributions summary:Mohammed primarily focused on improving the functionality and reliability of the `google-play-scraper` library. Their contributions involved fixing bugs related to the retrieval of app reviews and search results, ensuring the application handles edge cases gracefully, particularly when dealing with missing reviews or no search results. The user also fixed methods within the application, improving data retrieval and API functionalities. The commits demonstrate an understanding of the scraper's internal workings and a commitment to enhancing the library's stability and data accuracy.
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