Kun Yuan

Kun Yuan is an Assistant Professor in the Center for Machine Learning Research at Peking University. He received his B.S. degree in Telecommunication from Xidian University in 2011, M.S. degreee in Control Theory and Engineering from University of Science and Technology of China in 2014, and Ph.D. degree in Electrical and Computer Engineering from the University of California, Los Angeles (UCLA) in 2019. He was a staff algorithm engineer in the Decision Intelligence Lab at Alibaba (US) Group from 2019 to 2022, and a visiting researcher at École Polytechnique Fédérale de Lausanne (EPFL) in 2018.

Kun's research focuses on the theoretical and algorithmic foundations in optimization, signal processing, machine learning, and data science. He is currently dedicated to developing fast, scalable, reliable, and distributed algorithms for large-scale optimization, deep neural network training, federated learning, and the Internet of things. He received the IEEE Signal Processing Society Young Author Best Paper Award in 2018.

Homepage:  https://kunyuan827.github.io/

袁坤在北京大学国际机器学习研究中心任助理教授。他在2011年于西安电子科技大学通信工程系获得学士学位，2014年于中国科学技术大学自动化系获得硕士学位，2019年于美国加州大学洛杉矶分校电子与计算机工程系获得博士学位。他曾在2018年到瑞士洛桑联邦理工学院任访问研究员，2019年至2022年在阿里巴巴达摩院美国西雅图研究中心任高级算法专家。

袁坤主要从事最优化、信号处理、机器学习、数据科学等领域中的理论与算法研究。他目前主要关注如何为深度学习、联邦学习、以及边缘计算中的大规模问题设计快速且可靠的分布式优化与学习算法。他在2018年获得IEEE信号处理协会青年作者最佳论文奖。