[11/26] The Assisi seminar brings geosciences and humanities together to explore geoethics in a time of interconnected crises, including the responsible use of natural hazard forecasts.

[11/26] IHRR Visiting Associate Tunisha Gyawali begins her PhD in Civil and Environmental Engineering at UC Berkeley. Her research is going to focus on infrastructure sensing and modeling, advanced numerical computations, and geohazard mitigation to enhance infrastructure resilience.

[10/26] Researchers from the IHRR at Durham University and King’s College London have analysed lightning patterns within moving thunderstorms, developing computer simulations to help test methods for identifying lightning clusters.

[10/26] Prof Bruce D. Malamud joined an international workshop in Kerala, India, exploring cascading disaster impacts, engaging with community leaders and delivering training on the ethical use of AI.

[10/26] The Institute of Hazard, Risk and Resilience welcomes PhD researcher Emmanuel Dogbey, whose research explores natural hazards, critical infrastructure systems, and resilience-informed decision making.

[10/26] IHRR Professor Fausto Guzzetti joins an Italy-Japan field mission to investigate earthquake- and rainfall-induced landslides on the Noto Peninsula and strengthen international disaster-risk research.

[07/26] The British Council-funded RESILIENT project bridges engineering and social sciences to mitigate seismic risks in Türkiye's Urla district, fostering community-led heritage preservation and advancing UN-SDG 11 through transdisciplinary collaboration.

[09/26] Researchers from IHRR, Durham University Business School, Mathematical Sciences, Engineering, Computer Science and Earth Sciences met to explore new interdisciplinary research collaborations focused on risk, resilience and forecasting.

[09/26] At Trieste Next 2026, IHRR Professor Fausto Guzzetti will discuss how artificial intelligence can strengthen natural-hazard decisions without replacing human responsibility.

[09/26] With rapid advances in artificial intelligence, machine-learning models are increasingly challenging traditional physics-based approaches to forecasting complex systems. This is particularly visible in areas such as weather and climate prediction, where recent AI systems have demonstrated impressive forecasting skill. But does this mean that physical models should eventually be replaced by purely data-driven approaches?

[09/26] Xiangxue Lu is a Master’s student in Geological Engineering at Nanjing University, China, and is currently undertaking a six-month research visit at the Institute of Hazard, Risk and Resilience (IHRR), Durham University. Her visit provides an opportunity to develop new research ideas at the interface of geomorphological hazards, data-driven methods and environmental risk.

[09/26] A new paper co-authored by IHRR member Professor Fausto Guzzetti presents a Bayesian framework for rainfall-triggered landslide forecasts that explicitly accounts for uncertainty.