个人简介

专注于人工智能和机器学习的基础研究，主要包括深度神经网络的优化和泛化理论研究，以及深度神经网络在图像、视频和生物脑网络领域的应用。入选复旦新工科人才等多项人才计划。至今累计在国际人工智能/深度学习的顶级会议发表论文10余篇，并多次受邀进行主题报告。

研究兴趣：

深度神经网络

代表成果：

1.Ruizhe Zheng*, Jun Li*, Yi Wang, Tian Luo, Yuguo Yu. ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges, (AAAI Oral) 2023. (IF=25.57) (共同一作)

2.Tan Yu, Jun Li, Yunfeng Cai, Ping Li. Constructing Orthogonal Convolutions in an Explicit Manner, (ICLR) 2022. (IF=20.03)

3.Jianwen Xie, Yaxuan Zhu, Jun Li, Ping Li. A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model, (ICLR) 2022. (IF=20.03)

4.Jun Li, Sinisa Todorovic. Action Shuffle Alternating Learning for Unsupervised Action Segmentation, (CVPR) 2021. (IF=45.17)

5.Jun Li, Sinisa Todorovic. Anchor-Constrained Viterbi for Set-Supervised Action Segmentation, (CVPR) 2021. (IF= 45.17)

6.Jun Li, Sinisa Todorovic. Set-Constrained Viterbi for Set-Supervised Action Segmentation, (CVPR) 2020. (IF= 45.17)

7.Jun Li, Fuxin Li, Sinisa Todorovic. Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform, (ICLR) 2020. (IF=20.03)

8.Jun Li, Peng Lei, Sinisa Todorovic. Weakly Supervised Energy-Based Learning for Action Segmentation, (ICCV Oral) 2019. (IF=21.94)