黄奕晖，博士，讲师。2025年毕业于厦门大学电子科学与技术公司。2026年1月至今受聘于best365体育。
长期致力于人工智能技术、磁共振信号的重建与分析、医学信号处理等方向的研究。参与国家自然科学基金项目2项。发表期刊论文14篇，包括Science子刊Science Advances、人工智能顶刊IEEE Transactions on Neural Networks and Learning Systems等期刊，其中独立一作发表Science Advances 1篇。
【讲授课程】
本科生： 《面向对象程序设计》
研究生： 《现代信号处理》
【主要论文】（#表示共同作者）
[1]Yihui Huang, Yuncheng Gao, Zhangren Tu, Tatiana Agback, Vladislav Orekhov, Sven G. Hyberts, Gerhard Wagner, Yanqin Lin, Zhong Chen, Di Guo, and Xiaobo Qu*, Scalable deep learning reconstruction for accelerated multi-dimensional nuclear magnetic resonance spectroscopy of proteins, Science Advances, 11 (39): eadw8122, 2025.
[2]Yihui Huang#, Jinkui Zhao#, Zi Wang, Vladislav Orekhov, Di Guo and Xiaobo Qu*, Exponential signal reconstruction with deep Hankel matrix factorization, IEEE Transactions on Neural Networks and Learning Systems, 34 (9): 6214-6226, 2023.
[3]Xiaobo Qu*, Yihui Huang, Hengfa Lu, Tianyu Qiu, Di Guo, Tatiana Agback, Vladislav Orekhov and Zhong Chen*, Accelerated nuclear magnetic resonance spectroscopy with deep learning, Angewandte Chemie-International Edition, 59 (26): 10297-10300, 2020.
[4]Yihui Huang, Zi Wang, Xinlin Zhang, Jian Cao, Zhangren Tu, Meijin Lin, Lv Li, Xianwang Jiang, Di Guo, Xiaobo Qu*, Improve robustness to mismatched sampling rate: An alternating deep low-rank approach for exponential function reconstruction and its biomedical magnetic resonance applications, Journal of Magnetic Resonance, 376: 107898, 2025. (3区，IF 2.0)
[5]Chunyan Xiong, Mengxue Zhang, Tong Wei, Yihui Huang, Jian Cao, Qingrui Cai, Zhong Chen and Xiaobo Qu, Theoretical convergence analysis and initialization comparisons of deep soft-thresholding networks, IEEE Transactions on Neural Networks and Learning Systems, 37 (2): 951-965, 2026.
[6]Jian Cao, Chen Qian, Yihui Huang, Dicheng Chen, Yuncheng Gao, Jiyang Dong, Di Guo and Xiaobo Qu, A dynamics theory of RMSProp-based implicit regularization in deep low-rank matrix factorization, IEEE Transactions on Neural Networks and Learning Systems, 36 (10): 18750 - 18764, 2025.
[7]Zi Wang, Di Guo, Zhangren Tu, Yihui Huang, Yirong Zhou, Jian Wang, Liubin Feng, Donghai Lin, Yongfu You, Tatiana Agback, Vladislav Orekhov and Xiaobo Qu*, A sparse model-inspired deep thresholding network for exponential signal reconstruction-application in fast biological spectroscopy, IEEE Transactions on Neural Networks and Learning Systems, 34 (10): 7578-7592, 2023.
[8]Tianyu Qiu, Wenjing Liao, Yihui Huang, Jinyu Wu, Di Guo, Dongbao Liu, Xin Wang, Jian-Feng Cai, Bingwen Hu and Xiaobo Qu*, An automatic denoising method for NMR spectroscopy based on low-rank Hankel model, IEEE Transactions on Instrumentation and Measurement, 70: 1-12, 2021.
[9]Dicheng Chen, Wanqi Hu, Huiting Liu, Yirong Zhou, Tianyu Qiu, Yihui Huang, Zi Wang, Meijin Lin, Liangjie Lin, Zhigang Wu, Jiazheng Wang, Hao Chen, Xi Chen, Gen Yan, Di Guo, Jianzhong Lin and Xiaobo Qu, Magnetic resonance spectroscopy deep learning denoising using few in vivo data, IEEE Transactions on Computational Imaging, 9: 448-458, 2023.
【项目】
[1]国家自然科学基金委员会，面上项目，62071405，基于机器学习的多参数脑部定量磁化率成像研究，2021-01-01至2024-12-31，结题，参与。
[2]国家自然科学基金委员会，面上项目，61971361，基于稀疏表示的深度学习快速磁共振成像及应用，2020-01-01至2023-12-31，结题，参与。
