• 医学信号处理（深度学习，医疗影像大数据，影像组学，医学影像处理）
• 人工智能辅助诊断（基于磁共振、超声、CT的人工智能辅助诊断系统）
• 医学超声成像（成像原理、方法，非线性超声成像）

主持科研项目情况：

• 国家自然科学基金青年项目

• 中国博士后科学基金面上项目

• 国家自然科学基金重大研究计划

• 复旦大学人才引进项目

• 2022年 复旦大学优秀博士论文

• 2019年 飞利浦医疗产品创意大赛铜奖

• 2019年 上海市超级博士后

• 2019年 复旦大学优秀毕业生

• 2018年 博士国家奖学金

• 2017年 中国生物医学工程会议优秀论文奖

• 202203- ：复旦大学生物医学工程中心 青年副研究员

• 201907-202202：复旦大学电子科学与技术博士后流动站 博士后

• 201906-201906：复旦大学生物医学工程专业 博士学位

• 201309-201606： 重庆大学信号与信息处理专业 硕士学位

研究生课程：现代信息与信号处理理论

1. Wu Guoqing, Chen Xi, Shi Zhifeng，et al.,Convolutional neural network with coarse-to-fine resolution fusion and residual learning structures for cross-modality image synthesis. Biomedical Signal Processing and Control,2022,Volume 71, Part B.

2. Wu Guoqing#, Jiang Zhaoshun#, Cai Yuxi, et al. Multi-order brain functional Connectivity network-based Machine learning method for Recognition of delayed Neurocognitive recovery in older Adults undergoing non-cardiac Surgery. Frontiers in Neuroscience,2021:1-13.

3. Xiong Siyu#, Wu Guoqing#, Fan Xitian, et al. MRI‑based brain tumor segmentation using FPGA‑accelerated neural network. BMC Bioinformatics,2021:1-15.

4.  Wu Guoqing#, Chen Xi#, Lin Jixian# , et al. Identification of invisible ischemic stroke in noncontrast CT based on novel two-stage convolutional neural network model. Medical Physics, 2021, 48.

5. Pan Jiawei, Wu Guoqing, Yu Jinhua , et al. Detecting the Early Infarct Core on Non-Contrast CT Images with a Deep Learning Residual Network. Journal of Stroke and Cerebrovascular Diseases, 2021, 30(6):105752.

6. Wu Guoqing, Shi Zhifeng, Chen Yinsheng , et al. A Sparse Representation-based Radiomics for Outcome Prediction of Higher Grade Gliomas. Medical Physics, 2018, 46.

7. Wu Guoqing#, Lin Jixian#, Wang Yuanyuan* , et al. Early identification of ischemic stroke in noncontrast computed tomography. Biomedical Signal Processing and Control, 2019, 52(JUL.):41-52.

8. Wu Guoqing, Chen Yinsheng, Wang Yuanyuan*, , et al. Sparse representation-based radiomics for the diagnosis of brain tumors. IEEE Transactions on Medical Imaging, 2017.

9. 吴国庆, 李泽榉, 汪源源,等. 基于稀疏表示体系的原发性脑部淋巴瘤和胶质母细胞瘤图像鉴别. 生物医学工程学杂志, 2018, 35(5):7.

10. GuoqingWu, YuanyuanWang, JinhuaYu. 3D Texture Feature Learning for Noninvasive Estimation of Gliomas Pathological Subtype/ International MICCAI Brainlesion Workshop. Springer, Cham, 2018.

11. Wu Guoqing, Wang Yuanyuan*, Yu Jinhua* . Overall Survival Time Prediction for High Grade Gliomas Based on Sparse Representation Framework. Springer, Cham, 2017.

12. Liu Shujun*, Wu Guoqing, Liu Hongqing , et al. Image restoration approach using a joint sparse representation in 3D-transform domain. Digital Signal Processing, 2017, 60:307-323.

13. Liu Shujun*, Wu Guoqing, Zhang Xinzheng, et al. SAR despeckling via classification-based nonlocal and local sparse representation. Neurocomputing, 2016, 219(JAN.5):174-185.