Research Areas

Scientific Computing and Machine Learning; Theory, Algorithms, and Applications of Neural Networks; Numerical Methods for Partial Differential Equations

Education

2010-2014 Bachelor, Sichuan University

2014-2019 Doctor, Peking University

Work Experience

2025.2-present, Assistant Professor, YAU Mathematical Science Center, Tsinghua University

2022.7-2025.1, Research Scientist, King Abdullah University of Science and Technology

2020.8-2022.7, R. H. Bing Instructor Fellowship, University of Texas at Austin

2019.8-2020.7, Postdoc, Pennsylvania State University

Awards

2020-2022 R. H. Bing Fellowship, University of Texas at Austin

2017-2019 Ph.D. President Scholarship, Peking University

Publications

·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.