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Zixing received his Bachelor of Engineering from Southeast University in China, majoring in Computer Science. He then moved to Hong Kong and continued his academic journey at The Chinese University of Hong Kong, where he completed his doctoral studies in the Department of Computer Science and Engineering.

During his PhD, he conducted novel research focusing on the theoretical foundations of label-efficient learning on graph-structured data. This innovative framework demonstrates significant potential for interdisciplinary applications, with promising implications for social science, financial science, and material science research.

Currently, he works as a postdoctoral research associate in the Department of Engineering at the University of Cambridge where he continues to push the boundaries of machine learning. Simultaneously, his Junior Research Fellowship at ��ɫ��Ƶ underscores his commitment to advancing deep generative models, particularly in the emerging field of molecular science.