研究领域

最优化计算方法及理论、机器学习、人工智能

教育背景

2011-2015 学士 湖南大学

2015-2020 博士 北京大学

科研经历

2025/8 至今 助理教授，清华大学

2024-2025  博士后，加州大学伯克利分校

2022-2024  博士后，哈佛大学医学院

2021-2022  博士后，香港中文大学

荣誉与奖励

2024年 国际声学、语音与信号处理会议ICASSP 2024 唯一最佳论文奖

代表性论文

1. K. Deng, J. Hu†, J. Wu, Z. Wen, Oracle complexity of augmented Lagrangian methods for nonsmooth manifold optimization. Accepted at Mathematics of Operations Research (2025+).

2. J. Hu, T. Tian, S. Pan, Z. Wen, On the local convergence of the semismooth Newton method for composite optimization. Journal of Scientific Computing 103, 59 (2025).

3. J. Hu, J. Zhang, K. Deng, Achieving Local Consensus over Compact Submanifolds. IEEE Transactions on Automatic Control (2025).

4. Z. Deng, K. Deng, J. Hu†, Z. Wen, An Augmented Lagrangian Primal-Dual Semismooth Newton Method for Multi-block Composite Optimization. Journal of Scientific Computing, 102, 65 (2025).

4. K. Deng, J. Hu†, Decentralized projected Riemannian stochastic recursive momentum method for smooth optimization on compact submanifolds. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2025).

5. J. Zhang, J. Hu†, A. So, M. Johansson, Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data. Advances in Neural Information Processing Systems 37: Proceedings of the 2024 Conference (NeurIPS 2024).

6. J. Zhang, J. Hu, M. Johansson, Composite federated learning with heterogeneous data. ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024. won Best Paper Award! (Approximately 1/3000)

7. J. Wu, J. Hu†, H. Zhang, Z. Wen, Convergence analysis of an adaptively regularized natural gradient method. IEEE Transactions on Signal Processing, 72, pp.2527-2542 (2024).

8. J. Hu, K. Deng, J. Wu, Q. Li, A projected semismooth Newton method for a class of nonconvex composite programs with strong prox-regularity. Journal of Machine Learning Research, 25(56), 1-32 (2024).

9. J. Hu, R. Ao, A. M.-C. So, M. Yang, Z. Wen, Riemannian Natural Gradient Methods. SIAM Journal on Scientific Computing, 46(1), A204-A231 (2024).

10. J. Hu, X. Liu, Z. Wen, Y. Yuan, A Brief Introduction to Manifold Optimization, Journal of the Operations Research Society of China, 8, 199-248 (2020).

11. J. Hu, B. Jiang, L. Lin, Z. Wen, Y. Yuan, Structured Quasi-Newton Methods for Optimization with Orthogonality Constraints, SIAM Journal on Scientific Computing, 41(4), A2239-A2269 (2019).

12. J. Hu, A. Milzarek, Z. Wen, Y. Yuan. Adaptive Quadratically Regularized Newton Method for Riemannian Optimization. SIAM Journal on Matrix Analysis and Applications, 39(3), 1181-1207 (2018).