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Unveiling the Mystery of the Human Brain for AI Advancements

While machines can learn how to predict words, we have yet to understand how the human brain does it, and Dr LI Jixing’s research aims to uncover the secret

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Li's research applies computational models to understand how the human brain represents and computes information during language comprehension.

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Dr LI Jixing always imagined herself as a writer and that she would be doing something creative in languages one day. But little did she know that her creative journey would eventually lead her to the forefront of the world’s most cuttingedge research into computational neurolinguistics.

“When I began to realise that language is not an external object, but rather an internal object and a part of human cognition, I found that I was really interested in psychology, and this is where I developed a strong interest in psycholinguistics,” recounts the Assistant Professor at CityU’s Department of Linguistics and Translation and Assistant Professor (Affiliate) at the Department of Social and Behavioural Sciences.

Li kickstarted her educational career studying for her BA in English and Chinese at the Beijing Normal University. Then, with a newfound interest in language theories, she went to the UK to pursue her MA in Linguistics, from which she developed her strong interest in psycholinguistics. This eventually led her to complete a second master’s degree in Experimental Psychology at Oxford University and her PhD in Linguistics at Cornell. 

At the time, her intention was to just focus on psycholinguistics, but her advisor, Professor John HALE, was a computational linguist by training and was also doing fMRI experiments. Inspired, she ended up in computational neurolinguistics and her research today applies computational models to understand how the human brain represents and computes information during language comprehension.

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Li aspires to find an exciting community of like-minded fellows in academia for a deeper understanding of the human-machine interface.
Li aspires to find an exciting community of like-minded fellows in academia for a deeper understanding of the human-machine interface.
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