humanitarian response Archives - Dahdaleh Institute for Global Health Research /dighr/tag/humanitarian-response/ Effectiveness, equity, and excellent in global health. Fri, 21 Nov 2025 21:05:30 +0000 en-CA hourly 1 https://wordpress.org/?v=6.9.4 Reem Abu Shomar /dighr/person/reem-abu-shomar/ Fri, 07 Nov 2025 20:25:15 +0000 /dighr/?post_type=person&p=15097 Reem Abu Shomar is a global health researcher and innovator specializing in the intersection of water and health in conflict zones. Her work focuses on advancing evidence-based solutions to ensure equitable access to safe water and to address the critical role of water systems in shaping health outcomes. With a background that bridges research, practice, […]

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]]> Reem Abu Shomar is a global health researcher and innovator specializing in the intersection of water and health in conflict zones. Her work focuses on advancing evidence-based solutions to ensure equitable access to safe water and to address the critical role of water systems in shaping health outcomes. With a background that bridges research, practice, and innovation, she brings a transdisciplinary perspective to understanding the complex challenges at the nexus of water and community well-being, while mainstreaming gender and equity perspectives throughout her work.

Reem's professional experience includes designing and implementing innovative approaches to water and health challenges, working closely with communities, and translating knowledge into practical interventions. She is deeply committed to advancing global health equity by addressing the structural and environmental and social determinants of health, particularly in underserved and vulnerable populations, including those affected by conflict and displacement.

As both an intellectual and a practitioner, she combines critical problem-solving with collaboration across disciplines to produce meaningful and impactful outcomes. Her approach is rooted in reliability, evidence, and innovation, ensuring that the projects she undertakes are both academically rigorous and responsive to real-world needs.

Through her affiliation with the Dahdaleh Institute, Reem hopes to strengthen partnerships between research and practice, contribute to the vibrant scholarly community, and support collaborative initiatives that advance planetary health and global health equity. Her long-term aim is to further develop her research profile, publish collaboratively, and contribute to transformative global health scholarship that informs both policy and practice.

Research Keywords

Global Health, Water, Humanitarian response

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]]> Ali Rezaei /dighr/person/ali-rezaei/ Mon, 03 Nov 2025 18:23:30 +0000 /dighr/?post_type=person&p=15048 Ali Rezaei is a Research Assistant and Machine Learning Engineer at the Dahdaleh Institute for Global Health Research focused on retrieval-augmented generation for the Safe Water Optimization Tool. He builds end-to-end pipelines to ingest guidelines, field reports, and water-quality datasets, creates domain embeddings, and implements retrieval, reranking, and grounding so model outputs are traceable to […]

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]]> Ali Rezaei is a Research Assistant and Machine Learning Engineer at the Dahdaleh Institute for Global Health Research focused on retrieval-augmented generation for the Safe Water Optimization Tool. He builds end-to-end pipelines to ingest guidelines, field reports, and water-quality datasets, creates domain embeddings, and implements retrieval, reranking, and grounding so model outputs are traceable to sources. His work includes evaluation for factuality and latency, prompt and system design, and secure deployment in local and cloud environments. Ali collaborates with public-health and field partners to translate model outputs into operational recommendations and maintains clear documentation for reproducibility. He is completing a BSc Honours double major in Computer Science and Neuropsychology at 91راة« under Dr. Syed Imran Ali.

Research Keywords

Safe Water Optimization Tool; WASH; humanitarian response; water quality; chlorination; predictive modelling; time-series analysis; machine learning; large language models; decision support; public health; global health; 91راة«; Dahdaleh Institute

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