Ideas:
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As a computational scientist, I have always been working in the field of integrated natural resources management and modelling (INRMM) – particularly forests, soil, water resources. I use machine learning and advanced statistics in modular, semantically-enhanced modelling integrating uneven arrays of information (semantic array programming). Since several years, I focused on modelling forest tree species distribution and suitability in Europe, also under climate change – and forest resources disturbances (wildfires, forest pests), their effects on soil resources (soil erosion, landslides) and the transdisciplinary multiplicity of factors affecting natural disaster analysis, mitigation and management. I am interested in how to facilitate INRMM synergies, integration and scalability to better support policy-making for environmental sustainability and society resilience, and to help to move scientific research toward stronger robustness to uncertainty, reproducibility and cooperation
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