研究领域

科学计算与机器学习，神经网络的理论、算法与应用，偏微分方程数值方法

教育经历

2010-2014 学士 四川大学

2014-2019 博士 北京大学

科研经历

2025.2 至今 助理教授，清华大学丘成桐数学科学中心

2022.7-2025.1 研究科学家，阿卜杜拉国王科技大学

2020.8-2022.7 R. H. Bing讲师，得克萨斯大学奥斯汀分校

2019.8-2020.7 博士后，宾州州立大学

荣誉与奖励

2020-2022年 UT Austin R. H. Bing Fellowship

2017-2019年 北京大学校长奖学金

代表性论文

·G. Bao, Y. Zhao, J. He, Y. Zhang. Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection. ICLR 2025.

·J. He. On the Optimal Expressive Power of ReLU DNNs and Its Application in Approximation with Kolmogorov Superposition Theorem. IEEE Transactions on Neural Networks and Learning Systems, 2024.

·J. Liang, Z. Cai, J. Zhu, H. Huang, K. Zong, B. An, M. Alharthi, J. He, L. Zhang, H. Li, B. Wang and J. Xu. Alignment at Pre-training! Towards Native Alignment for Arabic LLMs. NeurIPS 2024.

·Y. Yang and J. He: Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss. ICML 2024.

·H. Huang, F. Yu, J. Zhu, X. Sun, H. Cheng, D. Song, Z. Chen, M. Alharthi, B. An, J. He, Z. Liu, Z. Zhang, J. Chen, J. Li, B. Wang, L. Zhang, R. Sun, X. Wan, H. Li, J. Xu. AceGPT, Localizing Large Language Models in Arabic. NAACL 2024.

·J. He, X. Liu and J. Xu. MgNO: Efficient Parameterization of Linear Operators via Multigrid. ICLR 2024.

·J. He and J. Xu. Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions. ArXiv:2312.14276, 2023.

·J. He, J. Xu, L. Zhang and J. Zhu. An Interpretive Constrained Linear Model for ResNet and MgNet. Neural Networks. 162: 384-392, 2023.

·J. He, R. Tsai and R. Ward. Side Effects of Learning from Low-dimensional Data Embedded in a Euclidean Space. Research in the Mathematical Sciences. 10(13), 2023.

·J. He, L. Li and J. Xu. ReLU Deep Neural Networks from the Hierarchical Basis Perspective. Computers & Mathematics with Applications. 120: 105-114, 2022.

·J. He, L. Li and J. Xu. Approximation Properties of Deep ReLU CNNs. Research in the Mathematical Sciences. 9(38), 2022.

·J. He, X. Jia, J. Xu, L. Zhang and L. Zhao. Make   Regularization Effective in Training Sparse CNN. Computational Optimization and Applications. 77: 163–182, 2020.

·J. He, L. Li, J. Xu, and C. Zheng. ReLU Deep Neural Networks and Linear Finite Elements. Journal of Computational Mathematics. 38(3): 502-527, 2020.

·J. He, K. Hu and J. Xu. Generalized Gaffney Inequality and Discrete Compactness for Discrete Differential Forms. Numerische Mathematik. 143: 781–795, 2019.

·J. He and J. Xu. MgNet: A Unified Framework of Multigrid and Convolutional Neural Network. Science China Mathematics. 62(7): 1331–1354, 2019.