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High Impact Thesis
High Impact Thesis

45. Kethmi Hettige - Physics-Guided AI: Understanding Time, Space, and the Real World

21 May 2026 1:10:47 NTU WOW

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About this episode

In this episode, we sit down with Kethmi Hettige, a Ph.D. candidate in Computing and Data Science at NTU, whose research focuses on spatial-temporal prediction and reasoning. Kethmi shares how her work combines AI, graph neural networks, physics-guided learning, and large language models to tackle real-world challenges such as air quality prediction, traffic forecasting, and environmental monitoring. We explore her research contributions, including the importance of interpretable and trustworthy AI systems, and integration of scientific knowledge into machine learning models. Beyond the technical discussion, Kethmi also reflects on her experiences throughout the Ph.D. journey.

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