孙淑婷

  • 政治面貌

    中共党员

  • 职称

    副教授、硕士生导师

  • 职务

  • 所在系所

    计算机应用技术研究所

  • 邮箱

    sst@lzu.edu.cn

  • 办公地址

    飞云楼513

学习经历

2010.09-2014.06 必赢nn699net 计算机科学与技术 工学学士
2014.09-2017.06 必赢nn699net 软件工程 工学硕士
2017.09-2021.06 必赢nn699net 计算机应用技术 工学博士

工作经历

2021.08-2023.09 北京理工大学医学技术学院 博士后
2023.10至今 必赢nn699net 副教授

教学情况

指导研究生情况

研究方向

1. 脑功能性疾病诊断与非药物干预
2. 电生理信号分析
3. 脑功能网络分析

招生专业

计算机相关专业

项目成果

目前在研项目:

1.科技创新2030-“脑科学与类脑研究”重大项目:抑郁症的前瞻性临床队列研究,2021ZD02006001, 参与

2.国家重大科研仪器研制项目:面向情感功能异常神经机制的多模态生理信息异步分析系统,62227807,参与

发表论文及专著

发表SCI/EI论文20余篇,近5年主要的SCI/EI论文如下(#为共同一作,*为通信作者):

期刊

1.Sun, S., Chen, H., Luo, G., Yan, C., Dong, Q., Shao, X., Li, X., & Hu, B. (2023). Clustering-Fusion Feature Selection Method in Identifying Major Depressive Disorder Based on Resting State EEG Signals.IEEE Journal of Biomedical and Health Informatics.

2.Sun, S., Qu, S., Yan, C., Luo, G., Liu, X., Dong, Q., & Li, X. (2023). A Study of Major Depressive Disorder Based on Resting-State Multilayer EEG Function Network.IEEE Transactions on Computational Social Systems.

3.Sun, S.#, Liu, L.#, Shao, X., Yan, C., Li, X., & Hu, B. (2022). Abnormal Brain Topological Structure of Mild Depression During Visual Search Processing Based on EEG Signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 1705-1715.

4.Sun, S., Yang, P., Chen, H., Shao, X., Ji, S., Li, X., ... & Hu, B. (2022). Electroconvulsive Therapy-Induced Changes in Functional Brain Network of Major Depressive Disorder Patients: A Longitudinal Resting-State Electroencephalography Study. Frontiers in Human Neuroscience, 16.

5.Chen, H.#, Sun, S.#, Li, J., Yu, R., Li, N., Li, X., & Hu, B. (2021). Personal-zscore: Eliminating individual difference for eeg-based cross-subject emotion recognition. IEEE Transactions on Affective Computing.

6.Sun, S., Li, X., Zhu, J., Wang, Y., La, R., Zhang, X., ... & Hu, B. (2019). Graph theory analysis of functional connectivity in major depression disorder with high-density resting state EEG data. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(3), 429-439.

7.Shao, X., Sun, S., Li, J., Kong, W., Zhu, J., Li, X., & Hu, B. (2021). Analysis of Functional Brain Network in MDD Based on Improved Empirical Mode Decomposition With Resting State EEG Data. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 1546-1556.

8.Liu, W., Dong, Q., Sun, S., Shen, J., Qian, K., & Hu, B. (2023). Risk Prediction of Alzheimer’s Disease Conversion in Mild Cognitive Impaired Population based on Brain Age Estimation. IEEE Transactions on Neural Systems and Rehabilitation Engineering.

9.Shao, X., Kong, W., Sun, S., Li, N., Li, X., & Hu, B. (2023). Analysis of functional connectivity in depression based on a weighted hyper-network method. Journal of Neural Engineering.

10.Cai, H., Yuan, Z., Gao, Y., Sun, S., Li, N., Tian, F., ... & Hu, B. (2022). A multi-modal open dataset for mental-disorder analysis. Scientific Data, 9(1), 178.

11.Shao, X., Yan, D., Kong, W., Sun, S., Liao, M., Ou, W., ... & Hu, B. (2023). Brain function changes reveal rapid antidepressant effects Of nitrous oxide for treatment-resistant depression: Evidence from task-state EEG. Psychiatry Research, 322, 115072.

12.Li, X., Zhang, X., Zhu, J., Mao, W., Sun, S., Wang, Z., ... & Hu, B. (2019). Depression recognition using machine learning methods with different feature generation strategies. Artificial intelligence in medicine, 99, 101696.

13.Li, X., La, R., Wang, Y., Niu, J., Zeng, S., Sun, S., & Zhu, J. (2019). EEG-based mild depression recognition using convolutional neural network. Medical & biological engineering & computing, 57, 1341-1352.

会议

1.Sun, S., Yan, C., Lyu, J., Xin, Y., Zheng, J., Yu, Z., & Hu, B. (2022, December). EEG Based Depression Recognition by Employing Static and Dynamic Network Metrics. In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1740-1744). IEEE. (CCF B类)

2.Sun, S., Chen, H., Shao, X., Liu, L., Li, X., & Hu, B. (2020, December). EEG based depression recognition by combining functional brain network and traditional biomarkers. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2074-2081). IEEE. (CCF B类)

3.Luo, G., Sun, S.*, Qian, K.*, Hu, B.*, Schuller, B., & Yamamoto, Y. (2023, July)., How does Music Affect Your Brain? A Pilot Study on EEG and Music Features for Automatic Analysis. In 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

4.Zhang, Y., Gong, T., Sun, S., Li, J., Zhu, J., & Li, X. (2020, December). A functional network study of patients with mild depression based on source location. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1827-1834). IEEE. (CCF B类)

5.Mao, W., Zhu, J., Li, X., Zhang, X., & Sun, S. (2018). Resting state eeg based depression recognition research using deep learning method. In Brain Informatics: International Conference, BI 2018, Arlington, TX, USA, December 7–9, 2018, Proceedings 11 (pp. 329-338). Springer International Publishing.

对外合作

荣誉获奖

社会工作

担任包括IEEE TAFFC、IEEE TCSS、IEEE TNSRE、JNE在内的多个期刊的审稿人。

其他信息

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