Dr. Amir Naghibi is a Professor (Associate) in the Division of Water Resources Engineering and the Center for Advanced Middle Eastern Studies (CMES) at Lund University, Lund, Sweden. His work sits at the intersection of Artificial Intelligence (AI), Computer Science, Remote Sensing, and Hydrology, addressing the water-climate-food-energy nexus. He designs and develops human-centered AI-driven decision support and policy modelling systems that translate complex environmental data into actionable intelligence for policymakers, water managers, and stakeholders bridging the gap between computational innovation and the socio-institutional contexts in which water governance decisions are made.

His institutional embedding in CMES and the MECW strategic research area (The Middle East in the Contemporary World), alongside scholars in political science, human geography, and conflict studies, reflects a sustained engagement with the social, political, and governance dimensions of water challenges, particularly in transboundary and fragile contexts. His recent research on translating AI-driven spatial analysis into governance-ready policy frameworks (Water Research, 2026) exemplifies this interdisciplinary approach.

Dr Naghibi has published more than 50 papers in peer-reviewed journals with over 7,000 citations leading to an H-Index of 34. He has been listed in Stanford University's "World's Top 2% Scientists" for six years from 2020 to 2025, demonstrating his broad and significant scientific influence.

He currently leads the AI and Decision Support System development in the Horizon Europe project FARMWISE (Future Agricultural Resource Management and Water Innovations for a Sustainable Europe), serving as WP leader and executive board member. In this capacity, he is responsible for designing an AI-based policy modelling system aligned with end-user decision-making workflows and stakeholder needs in agricultural water management. He also contributes to AGRILEAP, which employs co-creation methodologies for climate resilience in Swedish agriculture, and SWIFT, which addresses environmental monitoring under conditions of conflict and governance stress.

Dr. Naghibi teaches "Machine Learning for Water Engineers," "Water, Society, and Climate Change," and "Hydromechanics" at Lund University. His course "Water, Society, and Climate Change" addresses governance frameworks, equity, and the societal dimensions of climate adaptation. He developed and coordinated the PhD course "Machine Learning for Water Engineers," delivered four times across Lund University and SMHI, integrating theory with applied, problem-oriented learning.