School of biomedical engineering, Shanghai jiaotong university

Yao Li

Yao Li is a Professor and Doctoral Advisor at the School of Biomedical Engineering, Shanghai Jiao Tong University. She also serves as the Associate Director of the National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy at Shanghai Jiao Tong University.

She has been recognized as a Shanghai "Eastern Scholar" Distinguished Professor, a recipient of the Shanghai "March 8th Red Banner" Award, a "Guangci Scholar" at Ruijin Hospital, and a "Morning Star Scholar" at Shanghai Jiao Tong University.

Her research focuses on high-resolution in vivo imaging of neurometabolic function in the human brain and its applications in brain disease diagnosis. She has published over 150 research papers in leading academic journals such as Science, Nature Biomedical Engineering, Brain, Journal of Neuroscience, and Alzheimer's & Dementia.

Her work has received several prestigious awards, including:

• The 2023 ISMRM W. S. Moore Award from the International Society for Magnetic Resonance in Medicine (ISMRM)

• The 2023 Journal of Neuroscience Top 10 Spotlight of the Year

• The 2021 Best Paper Award (First Place) at the Annual Meeting of the International Society for Engineering in Medicine and Biology (EMBC)

• 20 ISMRM Annual Meeting Outstanding Abstract Awards (Summa Cum Laude & Magna Cum Laude Awards) from 2019 to 2024

She is currently an Associate Editor of BMC Neuroscience, a Senior Member of IEEE, a Lifetime Member of the World Association for Chinese Biomedical Engineers, a Committee Member of the Foreign Affairs Committee of the Chinese Society of Biomedical Engineering, and a Committee Member of the Brain Function Monitoring and Regulation Rehabilitation Committee of the Chinese Society of Rehabilitation Medicine.

Education

• BS in Electrical Engineering (1998-2002)
Department of Electrical and Information Engineering
Shanghai Jiao Tong University, Shanghai, China
• MS in Electrical Engineering (2002-2003)
Department of Electrical and Computer Engineering
State University of New York at Stony Brook, Stony Brook, NY, USA
• PhD in Electrical Engineering (2002-2008)
Department of Electrical and Computer Engineering
State University of New York at Stony Brook, Stony Brook, NY, USA

Work experience

• Assistant Professor (11/2010-03/2011)
Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
• Associate Professor (04/2011-12/2021)
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
• Professor (12/2021-present)
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

Research

High resolution magnetic resonance spectroscopic imaging; Deep learning based multimodal MR brain imaging, Brain mapping and neuroimaging of brain disorders

Research Project

Monograph

1. Y. Zhao, Y. Li, W. Jin, R. Guo, C. Ma, W. Tang, Y. Li, G. El Fakhri, Z.-P. Liang, Ultrafast J-resolved magnetic resonance spectroscopic imaging for high-resolution metabolic imaging of the brain. Nat. Biomed. Eng., In Press, 2025.

2. Ziwen Ke, Yue Guan, Tianyao Wang, Huixiang Zhuang, Zijun Cheng, Yunpeng Zhang, Jing-Ya Ren, Li Cao, Su-Zhen Dong, and Yao Li*, Fast and Stable Neonatal Brain MR Imaging Using Integrated Learned Subspace Model and Deep Learning, IEEE Transactions on Biomedical Engineering, In Press, 2025.

3. Hu J, Zhang M, Zhang Y, Zhuang H, Zhao Y, Li Y, Jin W, Qian XH, Wang L, Ye G, Tang H, Liu J, Li B, Nachev P, Liang ZP, Li Y*. Neurometabolic topography and associations with cognition in Alzheimer's disease: A whole-brain high-resolution 3D MRSI study. Alzheimers Dement. 2024 Sep;20(9):6407-6422.

4. Wang D, Fan Q, Xiao X, He H, Yang Y, Li Y*. Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms. Journal of Neuroscience. 2023 Oct 18;43(42):7016-7027. (2023 Top 10 JNeurosci Spotlight)

5. Ziyu Meng, Rong Guo, Tianyao Wang, Bin Bo, Zengping Lin, Yudu Li, Yibo Zhao, Xin Yu, David J Lin, Parashkev Nachev, Zhi-Pei Liang, Yao Li*, Prediction of Stroke Onset Time with Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping, IEEE Transactions on Biomedical Engineering, 2023 Nov;70(11):3147-3155.

6. Tianxiao Zhang, Yibo Zhao, Wen Jin, Yudu Li, Rong Guo, Ziwen Ke, Jie Luo, Yao Li* and Zhi-Pei Liang, B1 mapping using pre-learned subspaces for quantitative brain imaging, Magnetic Resonance in Medicine, 2023 Nov; 90(5):2089-2101.

7. Lin Z, Meng Z, Wang T, Guo R, Zhao Y, Li Y, Bo B, Guan Y, Liu J, Zhou H, Yu X, Lin D, Liang ZP, Nachev P, and Li Y*, Predicting the Onset of Ischemic Stroke With Fast High-Resolution 3D MR Spectroscopic Imaging, Journal of Magnetic Resonance Imaging, 2023 Sep, 58(3):838-847. (Cover Feature Article) (ISMRM W. S. Moore Award)

8. Zhang T, Guo R, Li Y, Zhao Y, Li Y*, Liang Z, T2’ mapping of the brain from water-unsuppressed 1H-MRSI and turbo spin-echo data, Magnetic Resonance in Medicine, 88(5): 2198-2207, 2022.

9. Zhang M, Guan Z, Zhang Y, Sun W, Li W, Hu J, Li B, Ye G, Meng H, Huang X, Lin X, Wang J, Liu J, Li B, Li Y*, Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease - A simultaneous resting-state FDG-PET/fMRI study, NeuroImage: Clinical, 34: 102977, 2022.

10. Li W, Xu J, Xiang Q, Zhuo K, Zhang Y, Liu D, Li Y*, Neurometabolic and functional changes of default-mode network relate to clinical recovery in first-episode psychosis patients: A longitudinal 1H-MRS and fMRI study, NeuroImage: Clinical, 34: 102970, 2022.

11. Ye Q, Zhang Z, Sun W, Fan Q, and Li Y*, Disrupted functional connectivity of precuneus subregions in obsessive-compulsive disorder. NeuroImage: Clinical 31: 102720, 2021.

12. Li Y*, Wang T, Zhang T, Lin Z, Li Y, Guo R, Zhao Y, Meng Z, Liu J, Yu X, Liang Z-P and Nachev P, Fast high-resolution metabolic imaging of acute stroke with 3D magnetic resonance spectroscopy, Brain (Cover Feature Article), 143(11): 3225–3233, 2020/11.

Contact

E-mail：yaoli@sjtu.edu.cn

telephone：86-21-62932981

address：教三楼南楼331室