2007/09-2011/07 中南大学 湘雅医学院 医学信息 学士学位

2011/09-2014/07 北京大学 软件与微电子学院 软件工程 硕士学位

2015/09-2019/07 北京大学 信息科学技术学院 智能科学与技术 博士学位

2019/07-2020/07 南京航空航天大学 计算机科学与技术学院 讲师

2020/07-2023/06 威尼斯7798cc 威尼斯7798cc 助理研究员

2023/06-今          威尼斯7798cc 威尼斯7798cc 副教授

研究生招生方向：深度学习训练算法

2023年度吴文俊人工智能自然科学一等奖（3/5）

专著：

• Zhouchen Lin, Huan Li and Cong Fang, Accelerated Optimization for Machine Learning-First-Order Algorithms. Springer, 2020.
  

• Zhouchen Lin, Huan Li and Cong Fang, Alternating Direction Method of Multipliers for Machine Learning. Springer, 2022.
  

部分论文：

• Huan Li and Zhouchen Lin, Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization. Journal of Machine Learning Research (JMLR), 25(274):1−52, 2024. (CCF A)

• Huan Li and Zhouchen Lin, Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ϵ −7/4 ) Complexity. Journal of Machine Learning Research (JMLR), 24(157):1−37, 2023. (CCF A. A short version appeared in ICML 2022)

• Huan Li, Zhouchen Lin and Yongchun Fang, Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization. Journal of Machine Learning Research (JMLR), 23(222):1-41, 2022. (CCF A)
  

• Huan Li, Cong Fang and Zhouchen Lin, Accelerated First-Order Optimization Algorithms for Machine Learning. Proceedings of the IEEE, 108(11):2067-2082, 2020. (CCF A)

• Huan Li and Zhouchen Lin, On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent. Journal of Machine Learning Research (JMLR), 21(33):1-45, 2020. (CCF A)

• Huan Li and Zhouchen Lin, Revisiting EXTRA for Smooth Distributed Optimization. SIAM Journal on Optimization (SIOPT), 30(3):1795-1821, 2020.

• Huan Li, Cong Fang, Wotao Yin and Zhouchen Lin, Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters. IEEE Transactions on Signal Processing (TSP), 68:4855-4870, 2020.

• Huan Li and Zhouchen Lin, Accelerated Proximal Gradient Methods for Nonconvex Programming. Advances in Neural Information Processing Systems (NIPS), 2015. (CCF A)

深度学习原理，本科生必修课