Understanding and predicting slope deformation is essential for reducing geohazard risks to communities and infrastructure. Machine learning, combined with monitoring data, offers new opportunities to improve our understanding and forecasting of slope movements. This talk will focus on three aspects: (i) exploring how water level changes and rainfall together can accelerate landslides, (ii) developing a new prediction model that blends physics-based understanding with machine learning to improve forecasting accuracy, and (iii) applying machine learning to a local case study, showing how monitoring data can support early warning and safer decision-making.

Hybrid Format!

The In-person component will be held at UNBC in the Teaching and Learning Building (building 10), Room 10-2522. Light refreshments will be provided for in-person attendees. 

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