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Communication and Information (WKWSCI) to integrate geospatial modelling, behavioural risk-perception research, agent-based simulation, and community engagement design in support of Singapore’s coastal
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the link between feedwater chemistry, foulant composition and cleaning performance across a range of industrial cases, the project aims first to establish the mechanisms of cleaning and, based on that
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applications based on this theory [2]. The ultimate goal of this project is to develop new computational methods for modelling social dilemmas that can account for real-world complexity in agents
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machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety : Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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Agent-Based Models, hydrological and flood models. GEB can simulate the dynamics between multiple hazard risk, how these risk impact society, vulnerability of different sectors, and how society can
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well established computational and mathematical modelling techniques to achieve its aims. Departure points are Evolutionary Game Theory and reinforcement learning, supported by agent-based
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efficiency, quality, and outcomes. A special focus is natural language processing (NLP) for health data, including large language models (LLMs) and agent-based frameworks. The project aims to develop
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empowering Texans through credible, research-based information and hands-on assistance. Our specialists lead damage assessments, coordinate emergency animal sheltering, provide critical resources, and
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multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers
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environments. The project will explore how learning-based and agentic AI systems (e.g., agents built on large language or foundation models) can be combined with physics-informed process models, digital