Yingjun’s research focus is meta-learning, a branch of Artificial Intelligence that teaches machines to learn with less and less data, rather than the current BigTech-trend of learning with more and more data and compute. Yingjun’s research line has been impressively productive, advancing the fields of meta-learning, few-shot learning, and learning with scarce data. His work has already led to 12 first-author papers in top-tier AI venues, a rare achievement in a field where 5 first-author publications are considered a strong PhD output. In recognition of the impact of his research, Yingjun previously received a CISCO Research Gift of 50,000 US dollars and the 2024 Chinese Government Award for Outstanding Self-Financed Students Abroad. Now he can add the distinction PhD cum laude to his achievements.

You can watch this PhD defence ceremony here.

You can find Yingjun’s dissertation in the UvA Dare database.