I build tools that turn messy educational-inequality data into something researchers can actually use.
I study Education at the University of Bristol and work as a Research Support Assistant in its School of Education, using Python, Docker, and interactive visualisation to turn complex, multi-source datasets into usable research infrastructure.
My research sits at the intersection of quantitative social research, data-informed education policy, and digital education. I am especially interested in whether AI-enabled scaffolding can recognise when a learner no longer needs support and step back accordingly — and, more broadly, in how AI may reshape education policy, learning environments, and cross-cultural learning.
Outside academia, I make a Chinese-language podcast, write poetry, and play music. These things are less separate from my research than they might appear.
我把复杂而杂乱的教育不平等数据,做成研究者真正用得上的工具。
目前在布里斯托大学攻读教育学,并在教育学院担任 Research Support Assistant。我使用 Python、Docker 和交互式数据可视化,将复杂的多源教育不平等数据转化为研究人员与公众都能使用的数字研究工具。
我的研究兴趣位于量化社会研究、数据驱动的教育政策与数字教育的交汇处。我尤其关注 AI 脚手架能否识别学习者何时已不再需要支持并主动渐退;也关心 AI 将如何重塑教育政策、学习环境与跨文化学习。
课堂之外,我做播客、写诗、也玩音乐。这些事和研究之间的距离,或许比表面上看起来要近一些。