CSDN Blog (Chinese)：https://blog.csdn.net/z_x_1996
2018-2021 M. Eng. School of Artificial Intelligence & Automation, HUST
2014-2018 B. Eng. School of Optical & Electronic Information, HUST
Generalization/Memorization in DNNs, Deep Learning, AI security, Brain-Computer Interfaces
- X. Zhang and D. Wu, “Empirical Studies on the Properties of Linear Regions in Deep Neural Networks,” in Proc. Int’l Conf. on Learning Representations (ICLR), Addis Ababa, Ethiopia, April 2020.
- X. Zhang and D. Wu, “Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs,” arXiv: 2004.13954, 2020.
- X. Zhang, D. Wu, L. Ding, H. Luo, C-T Lin, T-P Jung, R. Chavarriaga, “Tiny Noise Can Make an EEG-Based Brain-Computer Interface Speller Output Anything,” National Science Review, 2020, Major Revision.
- X. Zhang and D. Wu, “On the Vulnerability of CNN Classifiers in EEG-Based BCIs,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, vol. 27, no. 5, pp. 814-825, 2019.
- Z. Liu*, X. Zhang*, D. Wu, “Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs,” IEEE Trans. on Human-Machine Systems, 2019, Major Revision.
- X. Jiang, X. Zhang, D. Wu, “Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer Interfaces,” IEEE Symposium Series on Computational Intelligence, Xiamen, China, December 2019.
- 2020 Goodix Scholarship for Technology
- 2019 National Scholarship for Postgraduates
- 2019 1st Place – China Brain-Computer Interface Competition
- 2018 1st Place – IEEE WCCI Open Source Intelligence Discovery for Cybersecurity Threat
- 2018 3rd Place – Shenzhen International Competition for Medical and Health Big Data Innovative Application