Causal Discovery from Unstructured Data

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This Project aims to enable machines to discover causal relations from various kinds of unstructured data, such as images, text files, and sensor data. The project expects to promote causal revolution of data-centric intelligence and science – construct machines that can communicate in the language of cause and effect and answer ‘why’ questions by inferring from unstructured data. Expected outcomes of this project include theoretical foundations for causal discovery from unstructured data and practical algorithms that drive intelligent machines to make rational decisions in real-world scenarios. This should benefit society and the economy nationally and internationally through the applications of artificial intelligence and data science.