PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience (IMAGE)

The Hong Kong Polytechnic University

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

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Prof. Anqi Qiu, Professor of the PolyU Department of Health Technology and Informatics and Global STEM Scholar, has developed a novel “Hodge-Laplacian Heterogeneous Graph Attention Network” (HL-HGAT), revolutionising the modelling of complex relationships in graph-structured data. This innovation is poised to break through AI application limitations in fields such as neuroscience, logistics, computer vision and biology.

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