Jiangwei

2020.09 - 2025.06, Ph.D., Computer Science and Technology, Nanjing University.

    Supervisor: Professor Lijun Zhang (LAMDA Group).

    2023.10 - 2024.05, Visiting Student, National University of Singapore.

2016.09 - 2020.06, B.E., Computer Science and Technology, Xi'an Jiaotong University. 

    2019.01 - 2019.06, Exchange Student, University of California, Berkeley.

    2018.07 - 2018.08, Exchange Student, University of Manchester.

2025.10 - now, Nanjing University of Science and Technology.

    Professor, School of Computer Science and Engineering.

Reviewer for Conferences: 

    ICML 2025,2024,2023,2022; 

    NeurIPS 2024,2023,2022; 

    ICLR 2025,2024; 

    AAAI 2025; 

    AISTATS 2023.

Reviewer for Journal: 

    IEEE Transactions on Pattern Analysis and Machine Intelligence; 

    IEEE Transactions on Information Forensics and Security; 

    IEEE Transactions on Evolutionary Computation; 

    Scientific Reports;

    Machine Learning; 

    Applied Numerical Mathematics; 

    Information Sciences; 

    Neurocomputing; 

    Transactions on Machine Learning Research.

Machine Learning, Stochastic Optimization, LLM Optimization.

Distributed Optimization of Compositional Loss Functions. Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX24_0231) 2024.05-2025.05

9. Optimizing Unnormalized Statistical Models through Compositional Optimization. [link]

W. Jiang, J. Qin, L. Wu, C. Chen, T. Yang, and L. Zhang

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2026), 48(2): 1949 - 1960, 2026.

8. Revisiting Stochastic Multi-Level Compositional Optimization. [link]

W. Jiang, S. Yang, Y. Wang, T. Yang, and L. Zhang

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2025), 47(7): 5613 - 5624, 2025.

7. Normalized Adaptive Variance Reduction Method. [link]

W. Jiang, S. Yang, Y. Wang, and L. Zhang

Journal of Software, 36(11): 4893 - 4905, 2025.

6. Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions. [link]

W. Jiang, S. Yang, Y. Wang, and L. Zhang

In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), pages 22047 - 22080, 2024.

5. Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction. [link]

W. Jiang, S. Yang, W. Yang, and L. Zhang

In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), pages 33891 - 33932, 2024.

4. Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization.  [link]

W. Jiang, S. Yang, W. Yang, Y. Wang, Y. Wan, and L. Zhang

In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), pages 21962 - 21987, 2024.

3. Learning Unnormalized Statistical Models via Compositional Optimization.  [link]

W. Jiang, J. Qin, L. Wu, C. Chen, T. Yang, L. Zhang

In Proceedings of the 40th International Conference on Machine Learning (ICML 2023), pages 15105 - 15124, 2023.

2. Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization.  [link]

W. Jiang, G. Li, Y. Wang, L. Zhang, and T. Yang

In Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pages 32499 - 32511, 2022.

1. Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. [link]

W. Jiang, B. Wang, Y. Wang, L. Zhang, and T. Yang

In Proceedings of the 39th International Conference on Machine Learning (ICML 2022), pages 10195 - 10216, 2022.

Excellent Graduate of Nanjing University, 2025

National Scholarship, 2024

Excellent Student of Nanjing University, 2024

NeurIPS Top Reviewer, 2024

National Scholarship, 2023

Excellent Student of Nanjing University, 2023

LAMDA Elite Award, 2023

Tencent Scholarship, 2022

Excellent Student of Nanjing University, 2022

Industrial Bank Scholarship, 2021

Excellent Student of Nanjing University, 2021

Grand Champion of DeeCamp Artificial Intelligence Camp, 2020 (￥100,000)

Excellent Graduate of Xi'an jiaotong University, 2020