Date: 6th May 2026, Wednesday (9:30am – 10:00am)
Presenter: Detlef Stammer (Universität Hamburg)
Topic: Coastal System Responses to Global and Regional Sea Level Change

Abstract:
Dealing with SLR along coastlines around the world requires the development of a sea level simulation and information system that enables the development of actionable information for coastal decision making. Such a coastal digital twin should accomplish the simulations of all processes relevant for the impact of SLR on coastlines around the world under all possible CO2 emission scenarios. It would provide information required for mitigation and adaptation purposes. It would also enable the detection/attribution of observed sea-level transformations and their causes: climate related, vs resulting from other causes.
In a comparative study, drivers of sea level change (SLC) on coastal systems of Northern Europe (North and Baltic Seas) and Southeast Asia (SEA) are being reviewed that need to be realistically represented in a coastal digital twin and information system. Key drivers for open ocean SLC influencing coastlines include: (1) variations and trends in open ocean circulation, along with associated changes in heat and salinity; (2) ongoing terrestrial ice mass loss, which adds mass to the ocean; and (3) glacial isostatic adjustment (GIA) of the solid Earth. At the continental shelf and along coastlines, sea level is then additionally influenced by local processes including coastal currents and waves, and sediment transports. Superimposed are tides and storm surges, some of which are expected to change with climate, rising sea levels, and evolving coastlines. Local seal-level can strongly be influenced by vertical land motion (VLM) resulting from resource extraction (e.g., groundwater, gas or oil), sediment compaction, and/or tectonics.
Developing a costal digital information system requires an improved understanding of all these coastal processes and their proper presentation in numerical simulations, including the reaction of coastal sediments and ecosystems to SLR; it also needs to consider VLM, tectonics, and respective local and far-field reactions.

Date: 19th May 2026, Tuesday (11:00am – 12:00pm)
Presenter: Xiaoling Zhou (CCRS)
Topic: AI-based downscaling and inspection system: algorithms, workflow, and applications

Abstract:
Artificial intelligence (AI) is rapidly transforming the paradigm of scientific research and engineering applications. With its powerful capability in data modeling and complex pattern learning, AI has demonstrated significant impact in addressing real-world problems and enabling industrial intelligence. This talk focuses on the practical value of AI, highlighting how data-driven approaches enable two representative application domains: climate downscaling and building facade defect inspection.
First, a brief introduction to the speaker’s research background will be provided. The seminar will then present mainstream AI methods for climate downscaling, including convolutional neural networks (CNN), generative adversarial networks (GAN), diffusion models, and flow matching methods. Stochastic modelling approaches will also be presented. These methods aim to reconstruct high-resolution climate fields from coarse-resolution data while preserving physical consistency and capturing uncertainty.
Next, building facade defect inspection will be used as a case study to illustrate the complete workflow of AI model development from research prototype to real-world application. This includes problem definition and task formulation, data collection and preprocessing, model architecture selection and design, training strategy, performance evaluation and error analysis, and final API-based system deployment. Emphasis will be placed on model robustness and generalization in real-world application environments.
Overall, this seminar demonstrates how AI technologies can be effectively applied in both climate downscaling and urban infrastructure inspection, with a particular focus on the process from representative algorithms to model development and engineering applications.

Speaker Profile:
Dr. Xiaoling Zhou obtained her PhD from Tsinghua University in 2015. She possesses experience in AI model development and large-scale simulations. Her research includes investigating the impact of climate change on slope erosion in Singapore through statistical downscaling and developing AI-based systems for building defect inspection via a China–Singapore collaborative project. As a Principal Investigator, she has successfully led six projects, including those funded by the National Natural Science Foundation of China, focusing on modeling the properties of advanced structures and acoustic–structure systems using High-Performance Computing (HPC) platforms.
Recognized for her research contributions, Dr. Zhou was awarded the Shanghai Sailing Program for Young Talents in 2017, the Shanghai Quality Technology Excellence Award in 2019, and was selected for the AI Young Talent Pool at the China-Singapore International Research Institute in 2023. To date, she has published approximately 20 SCI papers as the first author and holds over 10 Chinese patents. Her current work focuses on integrating AI with climate science to provide smart solutions for a more resilient future.

Date: 26th May 2026, Tuesday (11:00am – 12:00pm)
Presenter: Muhammad RAHIZ (Aon)
Topic: Challenges in the Adoption of Climate Risks in Re/insurance

Abstract:
The seminar introduces the functions of the re/insurance industry, with discussion on how decisions are made and the challenges in adopting climate risks in the process. The first part of the seminar provides a practitioner’s insights on risk identification and quantification, drawing from tools such as hazard maps and probabilistic catastrophe models, and how their outputs provide perspectives on risk appetite. Hence, the need for risk transfer as a form of risk management. The second part of the seminar highlights the approaches the industry takes to navigate climate risks – both current and future. It identifies the challenges in adopting climate risks in decision making (including what works and what does not), and recommends a concerted effort from all stakeholders to address this fundamental issue.

Speaker Profile:
Dr Muhammad RAHIZ has a Doctor of Philosophy from Oxford University and post-qualification experience from Cape Town and Dubai. His research expertise is on the utility of climate model outputs in decision making in light of climate change, with focus on food and water security. His work has been published in Water Resources Management and International Journal of Climatology. He is in his ninth year in the re/insurance industry, having spent the first five in catastrophe flood model development and applications to disaster risk management and financing. He has been with Aon Reinsurance Solutions Asia since 2022 where he currently serves as Director for Catastrophe Management Analytics overlooking the Philippines, Vietnam, Thailand, and Pakistan. He is also a member of Aon’s climate risk advisory, formed to help clients assess and mitigate exposures to climate impacts through proven methodologies. He is also the regional lead for AI adoption at Aon.