姓名：王婷
技术职称：首聘副教授
学历学位：工学博士
导师类别：硕士生导师
联系电话：15360658360
邮箱：1007376724@qq.com
办公地点：工程学院南楼302
个人简介：
王婷，华南农业大学人工智能与低空技术学院首聘副教授，硕士生导师，华南理工大学博士、博士后，主要从事机器学习、深度网络、医学图像分析等相关领域的研究，已发表学术论文40余篇，其中包括IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Cybernetics、IEEE Transactions on Medical Imaging、IEEE Journal of Biomedical and Health Informatics 等国际顶级期刊论文，ICASSP、SMC、IJCNN 等国际顶级会议论文。主持国家自然科学基金青年项目、广东省自然科学基金面上项目、广东省区域联合基金青年项目。
招收专业：计算机技术、人工智能
教育经历：
2017-09至2021-06，华南理工大学，计算机科学与工程学院，博士
2014-09至2017-06，东北师范大学，信息科学与技术学院，硕士
2010-09至2014-06，贵州大学，计算机科学与信息学院，学士
工作经历：
2025年5月至今，华南农业大学，人工智能与低空技术学院，首聘副教授
2021-06至2025年2月，广州市第一人民医院（华南理工大学附属第二医院），华南理工大学医学院，博士后
研究领域：
深度网络优化（自编码器、宽度网络等）、医学图像分析（乳腺癌、阑尾炎、腹部多器官等）
承担科研项目情况：
1. 国家自然科学基金青年项目，基于CT影像解耦的多序列MRI腹部多器官分割关键技术研究，在研，主持
2. 广东省基础与应用基础研究基金面上项目，面向医学图像分割的深度注意力机制，在研，主持
3. 广东省基础与应用基础研究基金青年项目，面向多中心急性阑尾炎病理分型的鲁棒卷积网络，结题，主持
4. 中国博士后科学基金面上项目，高泛化可变卷积深度网络及其对急性阑尾炎术前分型研究，结题，主持
5. 国家自然科学基金面上项目，动态深度与宽度神经网络的泛化误差模型，结题，参与
6. 广东省省级科技计划项目（协同创新与平台环境建设专项，国际科技合作领域），基于多模态传感器的自适应人类行为识别框架及其在智能护理中的应用，结题，参与
代表性论著：
1. Y. Liang, W. Tang, Q. Kong, T. Wang(王婷)*, J. Zhang, W. W. Y. Ng, S. Chen, Y. Li, and Y. Guo, "Localized Intra- and Inter-tumoral Heterogeneity for Predicting Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer," IEEE Journal of Biomedical and Health Informatics (中科院1区top, IF: 6.8), Early Access, 2025.
2. Y. Liang, W. Tang, J. Zhang, T. Wang(王婷)*, W. W. Y. Ng, S. Chen, K. Jiang, X. Wei, X. Jiang, and Y. Guo, "XRadNet: A Radiomics-Guided Breast Cancer Molecular Subtype Prediction Network with a Radiomics Explanation," IEEE Journal of Biomedical and Health Informatics (中科院1区top, IF: 6.7), Accepted, 2025.
3. X. Zhang, J. Chen, Q. Li, J. Zhang, W. W. Y. Ng, and T. Wang(王婷), "LSSMSD: defending against black-box DNN model stealing based on localized stochastic sensitivity," International Journal of Machine Learning and Cybernetics (中科院3区, IF: 5.6), Early Access, 2024.
4. T. Wang(王婷), M. Zhang, J. Zhang, W. W. Y. Ng, and C. L. P. Chen,"BASS: Broad network based on localized stochastic sensitivity,"IEEE Transactions on Neural Networks and Learning Systems(中科院1区top, IF: 10.4), 2024.
5. T. Wang(王婷), S. Lu, J. Zhang, X. Liu, X. Tian, W. W. Y. Ng, and W. Chen, "SBHA: Sensitive binary hashing autoencoder for image retrieval,"IEEE Transactions on Cybernetics(中科院1区top, IF: 11.8), 2024.
6. T. Wang(王婷), W. W. Y. Ng, M. Pelillo, and S. Kwong, "LiSSA: localized stochastic sensitive autoencoders,"IEEE Transactions on Cybernetics(中科院1区top, IF: 11.8), 2021.
7. T. Wang(王婷), W. W. Y. Ng, J. Li, Q. Wu, S. Zhang, C. D. Nugent, and C. Shewell, "A deep clustering via automatic feature embedded learning for human activity recognition,"IEEE Transactions on Circuits and Systems for Video Technology (中科院1区top, IF: 8.4), 2022.
8. T. Wang(王婷), C. Lai, W. W. Y. Ng, K. Pan, M. Zhang, A. Vaccaro, and L. L. Lai, "Deep autoencoder with localized stochastic sensitivity for short-term load forecasting,"International Journal of Electrical Power and Energy Systems(中科院2区top, IF: 5.2), 2021.
9. Y. Liang, W. Tang, T. Wang*(王婷), W. W. Y. Ng, S. Chen, K. Jiang, X. Wei, X. Jiang, Y. Guo, "HRadNet: A Hierarchical Radiomics-based Network for Multicenter Breast Cancer Molecular Subtypes Prediction," IEEE Transactions on Medical Imaging (中科院1区top, IF: 10.6), 2024.
10. W. Li, T. Wang*(王婷), W. W. Y. Ng, "Population-based hyperparameter tuning with multitask collaboration,"IEEE Transactions on Neural Networks and Learning Systems(中科院1区top, IF: 10.4), 2023.
11. J. Zhang, T. Wang*(王婷), W. W. Y. Ng, and W. Pedrycz, "KNNENS: A k-nearest neighbor ensemble-based method for incremental learning under data stream with emerging new classes,"IEEE Transactions on Neural Networks and Learning Systems(中科院1区top, IF: 10.4), 2022.
12. W. W. Y. Ng, M. Zhang, andT. Wang*(王婷),"Multi-localized sensitive autoencoder attention-lstm for skeleton-based action recognition,"IEEE Transactions on Multimedia (中科院1区top, IF: 7.3), 2021.
13. J. Zhang,T. Wang*(王婷), W. W. Y. Ng, and W. Pedrycz, "Ensembling perturbation-based oversamplers for imbalanced datasets,"Neurocomputing (中科院2区top, IF: 6), 2022.
14. X. Zhang, C. Zhong, J. Zhang, T. Wang(王婷), and W. W. Y. Ng, "Robust recurrent neural networks for time series forecasting,"Neurocomputing (中科院2区top, IF: 6), 2023.
15. J. Zhang, T. Wang*(王婷), W. W. Y. Ng, and W. Pedrycz, "Perturbation-based oversampling technique for imbalanced classification problems,"International Journal of Machine Learning and Cybernetics (中科院3区, IF: 5.6), 2023.
16. W. Li, W. W. Y. Ng, T. Wang*(王婷), M. Pelillo, and S. Kwong, "HELP: An LSTM based approach to hyperparameter exploration in neural network learning,"Neurocomputing (中科院2区top, IF: 6), 2021.
17. C. S. Lai, Y. Yang, K. Pan, J. Zhang, H. L. Yuan, W. W. Y. Ng, Y. Gao, Z. Zhao,T. Wang(王婷), M. Shahidehpour, and L. L. Lai, "Multi-view neural network ensemble for short and mid-term load forecasting,"IEEE Transactions on Power Systems(中科院1区top, IF: 6.6),vol. 36, no. 4, pp. 2992-3003, 2021.
18. C. Zhong, C. S. Lai, W. W. Y. Ng, Y. Tao, T. Wang(王婷), and L. L. Lai, "Multi-view deep forecasting for hourly solar irradiance with error correction,"Solar Energy(中科院2区top, IF: 6.6), 2021.
19. W. W. Y. Ng, W. Zeng, and T. Wang*(王婷), "Multi-level local feature coding fusion for music genre recognition,"IEEE Access(中科院3区, IF: 3.9), 2020.
20. W. W. Y. Ng, S. Xu, T. Wang*(王婷), S. Zhang, and C. D. Nugent, "Radial basis function neural network with localized stochastic-sensitive autoencoder for home-based activity recognition,"Sensors (中科院3区, IF: 3.9), 2020.
21. C. Lai, Z. Mo, T. Wang*(王婷), H. Yuan, W. W. Y. Ng, and L. L. Lai, "Load forecasting based on deep neural network and historical data augmentation,"IET Generation Transmission & Distribution(中科院4区, IF: 2.5), 2020.
22. S. Zhang, W. W. Y. Ng, J. Zhang, C. D. Nugent, N. Irvine, and T. Wang(王婷), "Evaluation of radial basis function neural network minimizing L-GEM for sensor-based activity recognition,"Journal of Ambient Intelligence and Humanized Computing(中科院3区, EI论文), 2019.
23. M. Qi,T. Wang(王婷), F. Liu, B. Zhang, J. Wang, and Y. Yi, "Unsupervised feature selection by regularized matrix factorization,"Neurocomputing (中科院2区top, IF: 6), 2018.
主要授权专利、软件著作：
1． 吴永贤，何扬，王婷，钟灿琨；一种基于随机敏感度ST-SM的深度神经网络剪枝方法及系统，2024-03-22，中国，ZL 2021 1 0294928.5
2． 吴永贤，丘林，田星，张建军，王婷，余洪华；一种针对组织病理学图像的哈希样本平衡癌症标注方法，2023-12-19，中国，ZL 2021 1 0228166.9
3． 吴永贤，李金德，王婷；一种用于人物动作识别的深度聚类方法，2021-1-19，中国，ZL 2019 10166016.2
4． 易玉根，王建中，齐妙，王婷，郭常禄；一种无监督正则化矩阵分解特征选择方法，2021-1-8，中国，ZL 2017 1 0446167.4
