Vahid is an Economist/Data Scientist at Fera. He is the co-lead of Data, Modelling and Informatics interest group- a team of modellers, developers and scientists- at Fera with the purpose of advising Fera Director of Science in devising a data science roa
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Vahid is an Economist/Data Scientist at Fera. He has worked on a range of research areas including risk and uncertainty assessment, modelling adaptation of agriculture sector to climate change, resilience assessment of critical infrastructure, and development of decision support systems under deep/severe uncertainty. At Fera, he is engaged in socio-economic risk assessment of food fraud across European food supply chains, developing bespoke Early Warning Systems for food fraud detection, building decision support systems for pest and diseases, and building predictive models of sustainable yield intensification.
Vahid is the co-lead of Data, Modelling and Informatics interest group- a team of modellers, developers and scientists- at Fera with the purpose of advising Fera Director of Science in devising a data science roadmap for Fera.
Vahid is a fellow of Venice Centre of Climate Studies at Ca’Foscari University of Venice and served in the leadership of Society of Decision Making Under Deep Uncertainty. Vahid has authored or co-authored over 15 peer-reviewed papers, project reports and book chapters. He is also a member of Royal Economic Society, Society of Decision Making Under Deep Uncertainty, and American Economic Association.
Governments, local authorities, regulators and many businesses need to make decisions about the best use of finite resources to optimise social welfare or benefits for people, societies, the environment and the economy.
Our insights and support help organisations to optimise their economic resources in a complex, rapid- changing world. We work to understand the impact of external and internal drivers of change such as consumer behaviour, patterns of global trade, climate change, etc. on both societies and the environment – providing additional layers of evidence to inform policy decisions.
Mojtahed, V., Giupponi, C., Eboli, F., Bosello, F., and Carraro, C., (2016). Integrated Spatio‐temporal model of land‐use change: a focus on Mediterranean agriculture under global changes: In: Sauvage, S., Sánchez-Pérez, J.M., Rizzoli, A., (Eds.) Proceedings of the 8th International Congress on Environmental Modelling and Software, Toulouse, France, vol. 3, pp. 705. (ISBN: 978-88-9035-745-9).
Giupponi, C., Bernhofer, J., and Mojtahed, V. (2016). Uncertainty and resilience assessment of critical infrastructures: Application of the MCDA to Fiumicino airport: In: Sauvage, S., Sánchez-Pérez, J.M., Rizzoli, A., (Eds.) Proceedings of the 8th International Congress on Environmental Modelling and Software, Toulouse, France, vol. 2, pp. 562. (ISBN: 978-88-9035-745-9).
Balbi, S., Villa, F., Mojtahed, V., Hegetschweiler, K.,and Giupponi, C., (2016). A spatial Bayesian Network model to assess the benefits of early warning for urban flood risk to people, Natural Hazards and Earth System Sciences, Vol 16 pp. 1323–1337 (DOI:10.5194/nhess-16-1323-2016).
Giupponi, C., Mojtahed, V., Gain, A.K. and Balbi, S., Biscaro, C (2015). Integrated Risk Assessment of Water Related Disasters:.In: Hydro-Meteorological Hazards, and Disasters (Hazards and Disasters Series), Paron, P., Di Baldassarre, G., Shroder, J.F. (Eds.), Amsterdam, Elsevier, pp. 163-200. (ISBN 9780123948465).
Fekete, A., Tzavella, K., Armas, I., Binner, J., Garschagen, M., Giupponi, C., Mojtahed, V., Pettita, M., Schneiderbauer, S., Serre, D., (2015). Critical Data Source; Tool or Even Infrastructure? Challenges of Geographic Information Systems and Remote Sensing for Disaster Risk Governance, ISPRS Int. J. Geo-Inf, pp.1848-1869.(DOI 10.3390/ijgi4041848).
Early Warning System for food fraud detection; Decision Support Systems;
Risk and Uncertainty
Assessment; Economic Modelling.
We help societies to become more resilient or achieve the three pillars of sustainability through combining bottom and top-down decision making approaches under rapid socio-economic changes. Fera can help you to understand the likely impacts and cost-effectiveness of your decisions and actions, so you can make well-informed choices on how to deploy the economic resources available.
Protecting essential pollinators to support sustainable, high-quality crop production.
Fera is in a unique position to combine academic research, big data, forecasting models and information from a host of sources to inform practical environmental solutions and policy decisions across the public and private sector.
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