基本信息

王书强 研究员 博导  中国科学院深圳先进技术研究院

中科院特聘研究员,生物医学信息中心副主任。 于香港城市大学获得博士学位,先后在华为-诺亚方舟实验室、香港大学李嘉诚医学院和中科院深圳先进技术研究院从事机器学习、神经影像计算、脑机接口和大数据等领域的研究;主持科技部重点研发计划课题、国家自然科学基金(4项)、广东省杰出青年基金、广东省国际合作项目、深圳市科创委重点项目等20余项;授权美国发明专利14项,中国发明专利43项;在IEEE TPAMI, IEEE TMI, IEEE TIP, IEEE TNNLS, IEEE TCYB, IEEE TSMC, IEEE TNSRE, IEEE TSP, IEEE TAI, IEEE TCI, IEEE TMC, IEEE TCE, Medical Image Analysis 等国际权威期刊和ICLR, IJCAI, AAAI, MICCAI 等国际权威会议发表论文150余篇, 6篇论文入选ESI 高被引;H-index=47, 多次入选斯坦福大学“全球前2%顶尖科学家”年度科学影响力榜单和终身科学影响力榜单;担任Pattern Recognition, IEEE Transactions on Consumer Electronics, Brain Informatics,  Cognitive Neurodynamics, Frontiers in Neuroscience等SCI期刊副主编/编委。

邮箱: sq.wang@siat.ac.cn



Google Scholar Profile    

研究领域

机器学习,神经影像计算,脑机接口,医学人工智能,大数据分析技术


招生信息

招生专业
081203-计算机应用技术
招生方向
机器学习, 医学图像计算
脑网络计算
大数据分析技术

近五年代表性论文

  • Generative AI Empowers Brain-Computer Interfaces: A Review-Perspective on Technical Realities and Future Visions, IEEE Transactions on Consumer Electronics, DOI: 10.1109/TCE.2025.3650654, 2026
  • A New Brain Network Construction Paradigm for Brain Disorder via Diffusion-based Graph Contrastive Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):10389-10403, DOI:10.1109/TPAMI.2024.3442811
  • SCDM: Unified Representation Learning for EEG-to-fNIRS Cross-Modal Generation in MI-BCIs, IEEE Transactions on Medical Imaging,  DOI: 10.1109/TMI.2025.3532480, 2025
  • CATD: Unified Representation Learning for EEG-to-fMRI Cross-Modal Generation, IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2025.3550206, 44(7): 2757-2767, 2025
  • Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning,  IEEE Transactions on Consumer Electronics, 71(1):1034-1045. 2025
  • Prior-guided Adversarial Learning with Hypergraph for Predicting Abnormal Connections in Alzheimer's Disease, IEEE Transactions on Cybernetics, DOI:10.1109/TCYB.2023.3344641, 2024 
  • Alzheimer's Disease Diagnosis From Multi-modal Data via Feature Inductive Learning and Dual Multilevel Graph Neural Network, Medical Image Analysis, 97:103213,  2024
  • 3D Multimodal Fusion Network with Disease-induced Joint Learning for Early Alzheimer's Disease Diagnosis, IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2024.3386937. 2024
  • BDHT: Generative AI Enables Causality Analysis for Mild Cognitive Impairment, IEEE Transactions on Automation Science and Engineering, DOI: 10.1109/TASE.2024.3425949, 2024
  • Devignet: High-Resolution Vignetting Removal via a Dual Aggregated Fusion Transformer With Adaptive Channel Expansion, AAAI, 2024
  • WaveNet: Tackling Non-Stationary Graph Signals via Graph Spectral Wavelets, AAAI, 2024
  • DecGAN: Decoupling Generative Adversarial Network for Detecting Abnormal Neural Circuits in Alzheimer's Disease, IEEE Transactions on Artificial Intelligence, DOI: 10.1109/TAI.2024.3416420, 2024

  • Generative AI Enables Synthesizing Cross-Modality Brain Image via Multi-Level-Latent Representation Learning, IEEE Transactions on Computational Imaging, DOI:10.1109/TCI.2024.3434724
  • Estimating Addiction-Related Brain Connectivity by Prior-Embedding Graph Generative Adversarial Networks, IEEE Transactions on Cybernetics, DOI:: 10.1109/TCYB.2024.3353549, 2024
  • Fundus Image-label Pairs Synthesis and Retinopathy Screening via GANs with Class-imbalanced Semi-supervised Learning, IEEE Transactions on Medical Imaging, DOI:10.1109/TMI.2023.3263216, 2023 (IF=11)
  • Federated Domain Adaptation via Transformer for Multi-site Alzheimer’s Disease Diagnosis, IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2023.3300725, 2023  (IF=11)
  • 3D Brain Reconstruction by Hierarchical Shape-Perception Network from a Single Incomplete Image, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2023.3266819, 2023 (IF=14.2)
  • Alzheimer’s Disease Prediction via Brain Structural-Functional Deep Fusing Network, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31:4601-4612, DOI: 10.1109/TNSRE.2023.3333952, 2023
  • Brain Structure-Function Fusing Representation Learning using Adversarial Decomposed-VAE for Analyzing MCI, IEEE Transactions on Neural Systems and Rehabilitation Engineering, DOI: 10.1109/TNSRE.2023.3323432, 2023
  • Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain, IEEE Transactions on Neural Networks and Learning Systems, 34(11):8802-8814, 2023  (IF=14.2)
  • Large-Scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement, IJCAI 2023
  • Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN, IEEE Transactions on Neural Networks and Learning Systems,  DOI: 10.1109/TNNLS.2021.3118369, 34(8):4401-4415, 2023,  (IF=14.2 )
  • Joint 3D trajectory and resource optimization in multi-UAV enabled IoT networks with wireless power transfer, IEEE Internet of Things Journal, 8(10):7833-7848, 2021  (IF=10.2)
  • Effective Distributed Learning with Random Features: Improved Bounds and Algorithms, ICLR, 2021 
  • Tensorizing GAN with High-Order Pooling for Alzheimer’s Disease Assessment, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2021.3063516, 33(9): 4945-4959, 2022 (IF=14.2)
  • Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesis, IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2021.3107013, 41(1): 145-157, 2022,  (IF=11)
  • Predicting Clinical Scores for Alzheimer's Disease Based on Joint and Deep Learning, Expert Systems with Applications, 187:115966, 2022(IF=6.9 )
  • Insights Into Algorithms for Separable Nonlinear Least Squares Problems, IEEE Transactions on Image Processing, 30: 1207-1218, 2021(IF=10.3)
  • Diabetic Retinopathy Diagnosis using Multi-channel Generative Adversarial Network with Semi-supervision, IEEE Transactions on Automation Science and Engineering, 18(2):574-585, 2021, (IF=5.2)
  • An Ensemble based Densely-Connected Deep Learning System for Assessment of Skeletal Maturity, IEEE Transactions on Systems, Man and Cybernetics: Systems, 2022, 52(1):426-437, (IF=13.4)
  • Skin Lesion Segmentation via Generative Adversarial Networks with Dual Discriminators, Medical Image Analysis, 64: 10716, 2020 (IF=11.1)
  • Brain MR to PET Synthesis via Bidirectional Generative Adversarial Network, MICCAI 2020, LNCS 12262:698-707, 2020
  • Multi-Scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection, MICCAI 2020, LNCS 12267: 228–237, 2020.
  • Deep and joint learning of longitudinal data for Alzheimer’s disease prediction, Pattern Recognition, 10: 107247, 2020(IF=7.2)
  • Dominant-modes-based Sliding Mode Observer for Estimation of Temperature Distribution in Rapid Thermal Processing System, IEEE Transactions on Industrial Informatics, 15(5): 2673-2681,  2019 (IF:9.1 )

合作情况

   
项目协作单位

香港大学

香港城市大学

香港大学深圳医院

中山大学

指导学生

现指导学生

陈卓  硕士研究生  085211-计算机技术  

胡圣烨  硕士研究生  085210-控制工程  

罗蔚然  硕士研究生  085208-电子与通信工程  

奚桂锴  硕士研究生  085211-计算机技术  

游森榕  硕士研究生  085211-计算机技术  

胡博闻  硕士研究生  085211-计算机技术  

杨戈  硕士研究生  085211-计算机技术  

宫长威  硕士研究生  081200-计算机科学与技术  

荆常宏  硕士研究生  085400-电子信息  

王中昊  硕士研究生  085400-电子信息  

学生及毕业去向

杨胜,  2015,百度

卢哲,  2016,美国波士顿大学

程思潇,2017,阿里

王永灿,2017,科大讯飞

曹松,  2017,华为

吴昆,  2018,科大讯飞

王鸿飞,2018, 香港大学

王翔宇,2018,中国科技大学