GUAN Jiechao 管界超

管界超目前在香港科技大学（广州）担任博士后研究员，导师是熊辉教授。他分别于2023年和2018年在中国人民大学获得工学博士学位和理学学士学位。他的研究方向是机器学习理论与算法。具体而言，他专注于运用经典的学习理论工具（如函数空间复杂度理论、PAC-贝叶斯理论、算法稳定性理论、后悔界分析）为元学习提供改进的泛化误差上界，并通过最小化泛化误差上界来设计高效的元学习算法。

Jiechao Guan is currently a postdoctoral researcher at The Hong Kong University of Science and Technology (Guangzhou), under the supervision of Professor Hui Xiong. He received his PhD degree in 2023 and B.S. degree in 2018, both from Renmin University of China. His research interests are in machine learning theory and algorithms. In particular, he aim to provide improved generalization bounds for meta learning from the perspective of hypothesis space complexity, PAC-Bayes theory, algorithmic stability, or regret analysis, and develop efficient meta learning algorithms by minimizing the above genralization bounds.