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Homepage of Zi Wang(English, 中文) |
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| Ph.D. | ||||
| Department of Electronic Science,School of Electronic Science and Engineering (National Model Microelectronics College), Xiamen University. | ||||
| Email: wangziblake@gmail.com | ||||
| Computational Sensing Group, a part of Research Center of Magnetic Resonance and Medical Imaging at Xiamen University. | ||||
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Biosketch |
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Zi Wang obtained his Ph.D. in Electronic Science from Xiamen University in December 2024, and was a Visting Ph.D. at Imperial College London during 2024-2025. His research interests include computational MRI & MRS, biomedical signal processing, medical image analysis, and machine learning. Overall, they have published over 20 papers in top-tier peer-reviewed engineering and medical imaging journals and conference proceedings, including IEEE TMI/TNNLS/JBHI/SPM/TBME. Zi Wang has been the recipient of several prestigious awards, e.g., the OCSMRM Young Investigator Award (YIA), ISMRM Summa Cum Laude Merit Award (Top 3%), and Chinese National Scholarship. He has also served as a member of organizing committee in several international challenges, e.g., CMRxRecon 2023/2024. |
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Magnetic resonance spectroscopy and imaging | |
Machine learning and deep learning | ||||||
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Ph.D. Student (Sept. 2020-Dec. 2024) successive postgraduate and doctoral program Advisor: Xiaobo Qu Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, China |
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Visiting Ph.D. Student (Jan. 2024-Jan. 2025) China Scholarship Council Advisor: Guang Yang Department of Bioengineering, Imperial College London, United Kingdom |
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M.S. Student (Sept. 2019-July 2020) Postgraduate recommendation without examination Advisor: Xiaobo Qu Department of Electronic Science, Xiamen University, China |
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B.S. (Sept. 2015-July 2019) |
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| Professional Skills | |||||||||
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Deep learning framework: PyTorch, TensorFlow | ||||||||
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Mastered programming languages: Python, Matlab, C | ||||||||
| Selected Awards | |||||||||
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2024, OCSMRM Young Investigator Award (YIA) | ||||||||
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2024, ISMRM Summa Cum Laude Merit Award, Top 3% | ||||||||
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2022, Doctoral National Scholarship | ||||||||
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2021/2022, Xiamen University “The Merit Student” | ||||||||
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2021/2022/2023, ISMRM Educational Stipend | ||||||||
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2022, Liu Yubin Youth Science and Technology Scholarship of Xiamen University | ||||||||
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2018, Honorable Mention of the Mathematical Contest in Modeling (MCM) (1/3) | ||||||||
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2017, First Prize of the China Undergraduate Mathematical Contest in Modeling (Zhejiang Zone) (1/3) | ||||||||
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2017, Zhejiang Provincial Government Scholarship; First-class Scholarship of Zhejiang Gongshang University for Oversea Study | ||||||||
| (1) Journal Papers (#: Co-first authorship) | |||||||||
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Zi Wang, Chen Qian, Di Guo, Hongwei Sun, Rushuai Li, Bo Zhao, Xiaobo Qu, One-dimensional deep low-rank and sparse network for accelerated MRI, IEEE Transactions on Medical Imaging, 42: 79-90, 2023. (JCR 1, TOP, IF 10.6) | ||||||||
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Zi Wang, Di Guo, Zhangren Tu, Yihui Huang, Yirong Zhou, Jian Wang, Liubin Feng, Donghai Lin, Yongfu You, Tatiana Agback, Vladislav Orekhov, 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: 7578-7592, 2023. (JCR 1, TOP, IF 10.4) | ||||||||
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Zi Wang#, Haoming Fang#, Chen Qian, Boxuan Shi, Lijun Bao, Liuhong Zhu, Jianjun Zhou, Wenping Wei, Jianzhong Lin, Di Guo, Xiaobo Qu, A faithful deep sensitivity estimation for accelerated magnetic resonance imaging, IEEE Journal of Biomedical and Health Informatics, 28: 2126-2137, 2024. (JCR 1, TOP, IF 7.7) | ||||||||
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Dicheng Chen#, Zi Wang#, Di Guo, Vladislav Orekhov, Xiaobo Qu, Review and prospect: Deep learning in nuclear magnetic resonance spectroscopy, Chemistry -A European Journal, 26: 10391-10401, 2020. (JCR 2, TOP, IF 4.3) [Frontispiece] | ||||||||
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Qinqin Yang, Zi Wang, Kunyuan Guo, Congbo Cai, Xiaobo Qu, Physics-driven synthetic data learning for biomedical magnetic resonance: The imaging physics-based data synthesis paradigm for artificial intelligence, IEEE Signal Processing Magazine, 40: 129-140, 2023. (JCR 1, TOP, IF 14.9) [ESI Highly Cited Paper] | ||||||||
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Yihui Huang, Jinkui Zhao, Zi Wang, Di Guo, Vladislav Orekhov, Xiaobo Qu, Exponential signal reconstruction with deep Hankel matrix factorization, IEEE Transactions on Neural Networks and Learning Systems, 34: 6214-6226, 2023. (JCR 1, TOP, IF 10.4) | ||||||||
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Chen Qian, Zi Wang, Xinlin Zhang, Boxuan Shi, Boyu Jiang, Ran Tao, Jing Li, Yuwei Ge, Taishan Kang, Jianzhong Lin, Di Guo, Xiaobo Qu, A paired phase and magnitude reconstruction for advanced diffusion-weighted imaging, IEEE Transactions on Biomedical Engineering, 70: 3425-3435, 2023. (JCR 2, IF 4.6) | ||||||||
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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, Xiaobo Qu, Magnetic resonance spectroscopy deep learning denoising using few in vivo data, IEEE Transactions on Computational Imaging, 9: 448-458, 2023. (JCR 2, IF 5.4) | ||||||||
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Di Guo, Zhangren Tu, Yi Guo, Yirong Zhou, Jian Wang, Zi Wang, Tianyu Qiu, Min Xiao, Liubin Feng, Yuqing Huang, Donghai Lin, Yongfu You, Amir Goldbourt, Xiaobo Qu, XCloud-VIP: Virtual peak enables highly accelerated NMR spectroscopy and faithful quantitative measures, IEEE Transactions on Computational Imaging, 9: 1043-1057, 2023. (JCR 2, IF 5.4) | ||||||||
| (2) Conference Papers/Abstracts | |||||||||
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Zi Wang, Yirong Zhou, Chengyan Wang, Di Guo, Xiaobo Qu, Cardiac cine MRI with dimension-reduced deep separable spatiotemporal learning , International Society for Magnetic Resonance in Medicine Scientific Meeting (ISMRM), 2024, p. 0009. [Oral] [Summa Cum Laude Award] | ||||||||
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Zi Wang, Xiaotong Yu, Chengyan Wang, Weibo Chen, Jiazheng Wang, Ying-Hua Chu, Hongwei Sun, Rushuai Li, Peiyong Li, Fan Yang, Haiwei Han, Taishan Kang, Jianzhong Lin, Chen Yang, Shufu Chang, Zhang Shi, Sha Hua, Yan Li, Juan Hu, Liuhong Zhu, Jianjun Zhou, Meijing Lin, Jiefeng Guo, Congbo Cai, Zhong Chen, Di Guo, Xiaobo Qu, Physics-informed synthetic data learning boosts multi-scenario fast MRI reconstruction , International Society for Magnetic Resonance in Medicine Scientific Meeting (ISMRM), 2024, p. 0352. [Oral Power Pitch] | ||||||||
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Zi Wang, Haoming Fang, Chen Qian, Boxuan Shi, Lijun Bao, Liuhong Zhu, Jianjun Zhou, Wenping Wei, Jianzhong Lin, Di Guo, Xiaobo Qu, A faithful deep sensitivity estimation makes high-quality MRI reconstruction , International Society for Magnetic Resonance in Medicine Scientific Meeting (ISMRM), 2023, p. 3710. [Poster] | ||||||||
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Zi Wang, Chen Qian, Di Guo, Hongwei Sun, Rushuai Li, Xiaobo Qu, Memory-friendly and robust deep learning architecture for accelerated MRI , International Society for Magnetic Resonance in Medicine Scientific Meeting (ISMRM), 2022, p. 4301. [Power Pitch] | ||||||||
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Zi Wang, Yihui Huang, Zhangren Tu, Di Guo, Vladislav Orekhov, Xiaobo Qu, Accelerated magnetic resonance spectroscopy with model-inspired deep learning , International Society for Magnetic Resonance in Medicine Scientific Meeting (ISMRM), 2021, p. 1969. [Poster] | ||||||||
| (3)Preprints (#: Co-first authorship) | |||||||||
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Zi Wang, Xiaotong Yu, Chengyan Wang, Weibo Chen, Jiazheng Wang, Ying-Hua Chu, Hongwei Sun, Rushuai Li, Peiyong Li, Fan Yang, Haiwei Han, Taishan Kang, Jianzhong Lin, Chen Yang, Shufu Chang, Zhang Shi, Sha Hua, Yan Li, Juan Hu, Liuhong Zhu, Jianjun Zhou, Meijing Lin, Jiefeng Guo, Congbo Cai, Zhong Chen, Di Guo, Guang Yang, Xiaobo Qu, One for multiple: Physics-informed synthetic data boosts generalizable deep learning for fast MRI reconstruction, arXiv preprint, arXiv: 2307.13220, 2023. | ||||||||
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Zi Wang, Min Xiao, Yirong Zhou, Chengyan Wang, Naiming Wu, Yi Li, Yiwen Gong, Shufu Chang, Yinyin Chen, Liuhong Zhu, Jianjun Zhou, Congbo Cai, He Wang, Di Guo, Guang Yang, Xiaobo Qu, Deep separable spatiotemporal learning for fast dynamic cardiac MRI, arXiv preprint, arXiv: 2402.15939, 2024. | ||||||||
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Zi Wang#, Fanwen Wang#, Chen Qin, Shuo Wang, Jun Lyu, Yan Li, Cheng Ouyang, Haoyu Zhang, Kunyuan Guo, Zhang Shi, Qirong Li, Ziqiang Xu, Yajing Zhang, Hao Li, Sha Hua, Longyu Sun, Mengting Sun, Qin Li, Ying-Hua Chu, Wenjia Bai, Jing Qin, Xiahai Zhuang, Claudia Prieto, Alistair Young, Michael Markl, He Wang, Lianming Wu, Guang Yang, Xiaobo Qu, Chengyan Wang, CMRxRecon2024: A multi-modality, multi-view k-space dataset boosting universal machine learning for accelerated cardiac MRI, arXiv preprint, arXiv: 2406.19043, 2024. | ||||||||