Shuqiang Wang

Shuqiang Wang, PhD,  Professor, Deputy Director of Center for BIT.

 

He received his Ph.D degree from City University of Hong Kong, in 2012. He was a research scientist of Huawei Technologies Noah’s Ark Lab (2012-2013) and held a postdoctoral fellowship at the University of Hong Kong (2013-2014). He is currently an Professor with Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Science. He has pulished more than 100 SCI/EI papers on journals, such as IEEE TMI/TIP/TNNLS/TSMC/TSP//TII/TASE, Medical Image Analysis etc., and more than 30 patents; He served as an Associate Editor for Frontiers in Neuroscience, Brain Informatics, Big Data and Cloud Innovation; He was selected for "Top 2% Scientists Worldwide 2022"

Scopus: https://www.scopus.com/authid/detail.uri?authorId=53872228000

Research Areas:
Machine Learning, Brian Informatics, Medical Image Computing, Brian Informatics, Big Data

 

 

Selected publications since 2017

1.        Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain, IEEE Transactions on Neural Networks and Learning Systems, DOI:10.1109/TNNLS.2022.3153088, 2022  （IF=14.2)

2.        LAC-GAN: Lesion attention conditional GAN for Ultra-widefield image synthesis, Neural Networks, 2023, 158:89–98

3.        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, 2021,  （IF=14.2 )

4.        Multi-scale enhanced graph convolutional network for mild cognitive impairment detection, Pattern Recognition, 2023, 134, 109106，（IF=8.5,  Q1）

5.        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  Q1)

6.        Effective Distributed Learning with Random Features: Improved Bounds and Algorithms, ICLR, 2021

7.        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  Q1)

8.        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, Q1)

9.        Insights Into Algorithms for Separable Nonlinear Least Squares Problems, IEEE Transactions on Image Processing, 30: 1207-1218, 2021（IF=10.3 JCR Q1)

10.    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   Q1）

11.    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  Q1)

12.    Skin Lesion Segmentation via Generative Adversarial Networks with Dual Discriminators, Medical Image Analysis, 64: 10716, 2020 （IF=11.1，Q1)

13.    Brain MR to PET Synthesis via Bidirectional Generative Adversarial Network, MICCAI 2020, LNCS 12262:698-707, 2020

14.    Multi-Scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection, MICCAI 2020, LNCS 12267: 228–237, 2020.

15.    Deep and joint learning of longitudinal data for Alzheimer’s disease prediction, Pattern Recognition, 10: 107247, 2020（IF=8.5,  Q1）

16.    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  Q1）

17.    Subcarrier Pairing Based Resource Optimization for OFDM Wireless Powered Relay Transmissions with Time Switching Scheme, IEEE Transactions on Signal Processing, 65(5): 1130-1145, 2017. （IF:5.2 Q1）