(Canceled) CCSS Tutorial #2: Model-based analysis of tipping dynamics under uncertainty

Due to unforeseen circumstances, the speaker unfortunately had to cancel this tutorial, and there is NO replacement tutorial, as we received too many cancellations from the participants.

This half-day tutorial will be held in physical format at the CCSS Living Room (Min. 4.16) with lunch and refreshments provided. The overarching topic of the CCSS Events of the academic year 2025/2026 is Tipping behavior in Natural and Societal Systems. 

Please bring your own laptop with Python installed if you wish to take part in the group work after the talk.

Programme

• 12:00-13:00 Lunch
• 13:00-14:00 Introductory talk
• 14:00-14:15 Break / Group formation
• 14:30-16:30 Group work
• 16:30-17:00 Wrap-up 

Tutorial Overview
There is a growing attention for tipping points in socio-environmental systems. For example, last year there was the global tipping point report on governing earth system tipping points and both the risks and opportunities that these tipping points poses. Any model-based prospective assessment of tipping points, however, is subject to uncertainty. This uncertain can arise from unknowable future forcing conditions, but also from a lack of knowledge or fundamental disagreement amongst key actors on the inner workings of systems of interest. Drawing on exploratory modeling and related techniques from the literature on deep uncertainty, in this talk, I will introduce several techniques for model-based assessments of tipping dynamics under uncertainty.

Speaker Overview
Prof. dr. ir. Jan Kwakkel is full professor of Decision Making under Deep Uncertainty at TU Delft. His research interest is model-based support for decision making under deep uncertainty. His research focuses on the developing and testing innovative model-based techniques for the design of dynamic adaptive policy pathways. Within this, he is particularly interested in how to bring moral considerations into the quantitative analysis. He has applied his research in a range of domains including climate adaptation, flood risk management, transport and logistics, resource economics, and national safety and security. He is the lead developer of an open source workbench for exploratory modeling, scenario discovery, and multi-objective robust optimization. Next to his research on decision making under deep uncertainty, Jan also has an interested in text mining with a focus on analyzing scientific publications and patents.

To attend the talk and/or group work, please signup below before 15:00 on Tuesday March 31.