教育与工作经历

2010.09-2014.04  中南大学 测控技术与仪器 学士

2014.09-2020.06  清华大学 自动化系 博士 导师：游科友教授

2017.10-2018.10  比利时荷语鲁汶大学 电子系 联培博士  导师：Johan A.K. Suykens

2020.09-2023.08  比利时荷语鲁汶大学 电子系 博士后 导师：Johan A.K. Suykens

2023.09-2025.02  比利时荷语鲁汶大学 电子系 科研人员

2025.03-           威尼斯登录入口welcome 威尼斯登录入口welcome 准聘教授

研究方向

1. 神经网络建模与优化

2. 机器学习理论及应用

3. 具身智能与无人系统

更多研究工作详见：qinghua-tao.github.io

欢迎对我们研究工作感兴趣的本科生、硕士生、博士生及博士后与我邮件联系。

近5年承担的科研项目

1. 深度神经网络建模与优化，国家自然科学基金优秀青年科学基金项目（海外），2025-2027，主持

代表性学术论文

[1] Q. Tao, L. Li, X. Huang, X. Xi, S. Wang, and J.A.K. Suykens. "Piecewise Linear Neural Networks and Deep Learning," Nature Reviews Methods Primers, 2022. （影响因子：50.1）

[2] Q. Tao, F. Tonin, and J.A.K. Suykens. "Keynotes on Asymmetric Kernel SVD." Cybernetic and Intelligence, 2025.

[3] K. Fang*, Q. Tao*, X. Huang, and J. Yang. "Towards Robust Neural Networks via Orthogonal Diversity." International Journal of Computer Vision (IJCV), 2024.

[4] Q. Tao, F. Tonin, P. Patrinos, and J.A.K. Suykens. "Tensor-based Multi-view Spectral Clustering via Shared Latent Space." Information Fusion, 2024.

[5] Q. Tao*, F. Tonin*, A. Lambert, Y. Chen, P. Patrinos, and J.A.K. Suykens. "Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström Method." International Conference on Machine Learning (ICML), 2024.

[6] Y. Chen*, Q. Tao*, F. Tonin, and J.A.K. Suykens. "Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes." International Conference on Machine Learning (ICML), 2024.

[7] F. Tonin^§, Q. Tao^§, P. Patrinos, and J.A.K. Suykens. "Deep Kernel Principal Component Analysis for Multi-level Feature Learning." Neural Networks, 2024.

[8] K. Fang, Q. Tao^§, K. Lv, M. He, X. Huang, J. Yang^§, "Kernel PCA for Out-of-Distribution Detection", Advances in Neural Information Processing Systems (NeurIPS), 2024.

[9] Y. Chen*, Q. Tao*, F. Tonin, and J.A.K. Suykens. "Primal-attention: Self-attention through Asymmetric Kernel SVD in Primal Representation." Advances in Neural Information Processing Systems (NeurIPS), 2023.

[10] Q. Tao, Z. Li, J. Xu, S. Lin, B. De Schutter, and J.A.K. Suykens. “Short-term Traffic Flow Prediction Based on the Efficient Hinging Hyperplanes Neural etwork," IEEE Transactions on Intelligent Transportation Systems, 2022.

[11] D. Li*, Q. Tao*, J. Liu, and H. Wang. "Center-aware Adversarial  Autoencoder for Anomaly Detection." IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 6, pp. 2480-2493, 2022.

[12] Q. Tao, J. Xu, Z. Li, N. Xie, S. Wang, X. Li, and J.A.K. Suykens. "Toward Deep Adaptive Hinging Hyperplanes," IEEE Transactions on Neural Networks and Learning Systems, 2021.

[13] Q. Tao, Z. Li, J. Xu, N. Xie, S. Wang, and J.A.K. Suykens. “Learning with Continuous Piecewise Linear Decision Trees,” Expert Systems with Applications,” 2020.

[14] Q. Tao, X. Huang, S. Wang, and L. Li. “Adaptive Block Coordinate DIRECT Algorithm,” Journal of Global Optimization,  2017.

[15] Q. Tao, X. Huang, S. Wang, X. Xi, and L. Li. “Multiple Gaussian Graphical Estimation with Jointly Sparse Penalty,”  Signal Processing, 2016.

[16] T. Li, Q. Tao, W. Yan, Y. Wu, Z. Lei, K. Fang, M. He, X. Huang. "Revisiting Random Weight Perturbation for Efficiently Improving Generalization." Transactions on Machine Learning Research (TMLR), 2024.

[17]  K. Fang, Q. Tao, Y. Wu, T. Li, J. Cai, F. Cai, X. Huang, and J. Yang. "Towards Robust Neural Networks via Orthogonal Diversity." Pattern Recognition, vol. 149, pp. 110281, 2024.

[18] J. Xu, Q. Tao, Z. Li, X. Xi, J.A.K. Suykens, and S. Wang. “Efficient Hinging Hyperplanes Neural Network and its Application in Nonlinear System Identification.” Automatica, vol. 116, pp. 108906, 2020.

*共同一作（equal contribution）； § 通讯作者（corresponding author）

授权国家发明专利及出版专著

专著

科研获奖

讲授课程、出版教材及教学成果

讲授课程

出版教材

教学成果

学术兼职

国际会议委员： The IFAC Workshop on Control for Smart Cities 2025, Machine Learning Journal Track in IEEE International Conference on Data Science and Advanced Analytics 2024.

论坛组织者：International Workshop on Deep Learning and Kernel Machines 2024; Workshop on Rethinking Transformers through Duality and New Directions 2024.

期刊审稿⼈：Machine Learning、Neural Networks、Pattern Recognition Letters、IEEE TIP、IEEE TNNLS、IEEE SPL、IEEE TASE、IEEE TCSVT等.

会议审稿⼈：NeurIPS、ICML、ICLR、ICASSP、CDC、ACC等.