Amir Hassani
Scientist
+47 967 09 413
+47 63 89 80 17
Urban Environment and Industry
Kjeller
ahas@nilu.no
Amir is an Environmental Data Scientist with a PhD from the University of Manchester, where his research focused on modelling large-scale processes near Earth’s surface, particularly under current and projected climate conditions.
At NILU, his research is currently focused on enhancing the utility of novel low-cost sensor networks by integrating data from static, mobile, and wearable sensors with complementary datasets such as satellite remote sensing, air quality models, and citizen-contributed information.
His core competencies include machine learning, spatial analysis, and statistical data analytics, all of which he applies to investigate the physical, human, and policy dimensions of global environmental change. He is particularly interested in the drivers and impacts of changes in areas such as air quality, climate, urbanization, biodiversity, and ecosystem services. His work supports theoretically and empirically robust insights to advance knowledge on environmental change and its implications for society.
Amir is an Environmental Data Scientist with a PhD from the University of Manchester, where his research focused on modelling large-scale processes near Earth’s surface, particularly under current and projected climate conditions.
At NILU, his research is currently focused on enhancing the utility of novel low-cost sensor networks by integrating data from static, mobile, and wearable sensors with complementary datasets such as satellite remote sensing, air quality models, and citizen-contributed information.
His core competencies include machine learning, spatial analysis, and statistical data analytics, all of which he applies to investigate the physical, human, and policy dimensions of global environmental change. He is particularly interested in the drivers and impacts of changes in areas such as air quality, climate, urbanization, biodiversity, and ecosystem services. His work supports theoretically and empirically robust insights to advance knowledge on environmental change and its implications for society.