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Das-Boot/README.md

Hi there 👋

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I'm Zhaoning!

  • 👣 I am a second-year PhD student working with Prof. Haiyan Wu in Affective, Neuroscience and Decision-making Laboratory (A. N. D Lab) in the psychology program at the University of Macau (Macao, China).

    Before that, I was a research assistant supervised by Prof. Yixuan Ku in Memory and Emotion Laboratory (MELab) at the Department of Psychology, Sun Yat-Sen University (SYSU, Guangzhou, China). Before joining this lab, I worked as an NLP engineer in the Department of Big Data and Artificial Intelligence at Tianpeng Technology Co., Ltd (Guangzhou, China).

    I received a B.E. degree in Information Security in 2016 and an M.E. degree in Software Engineering in 2018, both from SYSU.

  • 💡 Enlightened by Heinrich Heine's famous quote, 'Thought precedes action, as lighting does thunder', I devoted myself to theoretical research after familiarising myself with empirical research and application. Specifically, I aspire to make contributions to a 'virtuous circle' in which shared insights into artificial intelligence and social psychology will advance the development of both fields.

  • 🌊 Research interests: Social cognition, social neuroscience, mentalising, artificial social intelligence, natural language processing

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Recent Research Articles


Pinned

  1. bot_or_not bot_or_not Public

    Code and data for paper 'Towards human-compatible autonomous car: A study of non-verbal Turing test in automated driving with affective transition modelling'

    Jupyter Notebook 3 1

  2. andlab-um/trinity andlab-um/trinity Public

    Code and data for paper 'Every individual makes a difference: A trinity derived from linking individual brain morphometry, connectivity and mentalising ability'

    MATLAB 4

  3. scite scite Public

    Code and data for paper 'Causality extraction based on self-attentive BiLSTM-CRF with transferred embeddings'

    Jupyter Notebook 60 15

  4. eason eason Public

    Code and data for paper 'Fine-tuning ERNIE for chest abnormal imaging signs extraction'

    Python 3