胡国强

研究领域

所属学科及方向：人工智能学科（脑与认知科学）

研究方向：脑信号分析与处理、神经影像、功能性磁共振成像、盲源分离、张量分解

教育背景

工作经历

教育教学情况

1、承担课程情况

2、出版教材情况

暂无

3、承担教改项目情况

暂无

4、发表教改论文情况

暂无

科学研究情况

1、承担项目情况

暂无

2、发表学术论文情况

[1] Guoqiang Hu, Huanjie Li, Wei Zhao, et al. Discovering Hidden Brain Network Responses to Naturalistic Stimuli via Tensor Component Analysis of Multi-Subject FMRI Data. NeuroImage, 2022, 255:119193.

[2] Guoqiang Hu, Abigail B Waters, et al. Snowball ICA: A Model Order Free Independent Component Analysis Strategy for Functional Magnetic Resonance Imaging Data. Frontiers in Neuroscience, 2020, 14:569657.

[3] Guoqiang Hu, Deqing Wang, et al. Frequency specific co-activation pattern analysis via sparse nonnegative tensor decomposition. J. Neurosci. Methods, 2021, 362:109299

[4] Guoqiang Hu, Qing Zhang, Abigail B. Waters, et al. Tensor clustering on outer-product of Coefficient and Component Matrices of Independent Component Analysis for Reliable Functional Magnetic Resonance Imaging Data Decomposition. J. Neurosci. Methods, 2019, 325:108359

[5] Guoqiang Hu, Tianyi Zhou, Siwen Luo, et al. Assessment of Nonnegative Matrix Factorization Algorithms for Electroencephalography Spectral Analysis. BioMedical Engineering OnLine, 2020, 19(1):61.

[6] Qing Zhang*, Guoqiang Hu*, Lili Tian, et al. *共同第一作者，Examining Stability of Independent Component Analysis based on Coefficient and Component Matrices for Voxel-based Morphometry of Structural Magnetic Resonance Imaging, Cognitive Neurodynamics, 2018, 12(5):461-470.

[7] Wei Zhao, Huanjie Li, Guoqiang Hu, et al. Consistency of Independent Component Analysis for FMRI. Journal of Neuroscience Methods, 2021, 351:109013.

[8] Wei Zhao, Huanjie Li, Yuxing Hao, Guoqiang Hu, et al. An efficient functional magnetic resonance imaging data reduction strategy using neighborhood preserving embedding algorithm, Human Brain Mapping, 2021, 43(5):1561-1576.

3、获得授权专利情况

暂无

4、出版学术专著情况

暂无

硕士生招生情况

1、研究生招生学科、招生方向和名额

招生学科：人工智能、大数据技术与工程

研究方向：人工智能理论基础、脑信号分析与处理

2、研究生招生要求

良好的编程、英语基础，扎实的专业背景，精益求精的精神，对探索的热爱。