Personal Information

Dr. Hu is a full-time faculty member and Master's supervisor in the Department of Computer Science and Technology at Nanchang University. He received his Ph.D. in Science from Tongji University in July 2021. From September 2018 to September 2019, he was sponsored by the China Scholarship Council (CSC) for a joint-training program at Politecnico di Torino in Italy.

In recent years, he has led research projects funded by the National Natural Science Foundation of China, the Natural Science Foundation of Jiangxi Province, and the Young Talent Cultivation and Innovation Fund of Nanchang University. He has also participated in several national and provincial research initiatives and has published more than 20 peer-reviewed SCI-indexed papers, including those recommended by the CCF. Additionally, he holds one invention patent as the first inventor.

Dr. Hu teaches undergraduate courses such as "Data Structures" and "Artificial Intelligence," as well as the graduate-level course "Machine Learning." He has presided over and completed an industry-academia collaborative education project supported by the Ministry of Education.

Currently, his research focuses on interdisciplinary areas integrating artificial intelligence with ground penetrating radar and seismic surface waves. He works on the design and training of deep neural network architectures guided by physical priors, aiming to address computational imaging challenges in fields such as underground space exploration.


Scientific Research Achievements

2025:

[1] Shufan Hu*, Huilin Zhou, Laura Valentina Socco and Yonghui Zhao*, "Attention Mechanism-Based Improvement of Stacked Surface Wave Cross-Correlation From High-Frequency Ambient Noise," in IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-15, 2025, Art no. 5914815, doi: 10.1109/TGRS.2025.3574957. 


2024:

[1] Shufan Hu*, Huilin Zhou, Yonghui Zhao, Wei Cai and Kunwei Feng, "Indicator-guided Multifrequency GPR Data Fusion with Transformer," in IEEE Transactions on Geoscience and Remote Sensing,  vol. 62, pp. 1-13, 2024, Art no. 5921413, doi: 10.1109/TGRS.2024.3432933.

[2] Huilin Zhou*, Ting Xie, Qiegen Liu and Shufan Hu*, "An Augmented Lagrangian Method-Based Deep lterative Unrolling Network for Seismic Full-Waveform Inversion," in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp.1-13, 2024, Art no. 5914613, doi: 10.1109/TGRS.2024.3397832.

[3] Huilin Zhou, Chenglin Xu, Yang Cheng, Qiegen Liu, Shufan Hu and Yuhao Wang*, "Self-Supervised Learning of Physics-Guided Deep Unfolding Parallel Networks for Solving Nonlinear Inverse Scattering Problems," in IEEE Transactions on Microwave Theory and Techniques, vol. 72, no. 9, pp. 5204-5217, Sept. 2024, doi: 10.1109/TMTT.2024.3368452.