Xiaolin Hu Ph.D.
Associate Professor(tenured), Department of Computer Science and Technology, Tsinghua University
Dr. Hu received his PhD degree in Automation and Computer-Aided Engineering from The Chinese University of Hong Kong in 2007, under the supervision of Prof. Jun Wang. He proceeded to become a post-doc researcher at the Department of Computer Science and Technology, Tsinghua University working with Prof. Bo Zhang. Since 2009, Dr. He has been a faculty member of the Department of Computer Science and Technology, Tsinghua University, working in the TSAIL group directed by Prof. Bo Zhang and Prof. Jun Zhu.
Degrees
The Chinese University of Hong Kong, Ph.D., 2007
Wuhan University of Technology, M.S. 2004
Wuhan University of Technology, B.S., 2001
Appointments
2013 - present Associate Professor, Tsinghua University
2009 – 2013 Assistant Professor, Tsinghua University
2007 – 2009 Postdoctoral Fellow, Tsinghua University
Research Interests and Fields
Deep learning, computational neuroscience.
Dr. Hu’s research interests lie in below two areas. Firstly, adversarial attack and defense of deep learning models. Secondly, brain-inspired computational models to circumvent the limitations current deep learning models are facing.
Selected Publications
[1] Gang Zhang Junnan Chen, Guohuan Gao, Jianmin Li, Si Liu, Xiaolin Hu*, “SAFDNet: A simple and effective network for fully sparse 3D object detection,” Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 17-21, 2024. (Oral, acceptance rate0.7%)
[2] Kai Li, Fenghua Xie, Hang Chen, Kexin Yuan*, Xiaolin Hu*, “An audio-visual speech separation model inspired by cortico-thalamo-cortical circuits,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 10, pp. 6637-6651, Oct 2024.
[3] Kai Li, Runxuan Yang, Fuchun Sun, Xiaolin Hu*, “IIANet: an intra- and inter-modality attention network for audio-visual speech separation,” The 41st International Conference on Machine Learning (ICML), Vienna, Austria, July 21-27, 2024.
[4] Xiao Li, Ziqi Wang, Bo Zhang, Fuchun Sun, Xiaolin Hu*, “Recognizing object by components with human prior knowledge enhances adversarial robustness of deep neural networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 7, pp. 8861-8873, 2023.
[5] Jianfeng Wang, Xiaolin Hu*, “Convolutional neural networks with gated recurrent connections,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 7, pp. 3421-3425, 2022.
[6] Zhanhao Hu, Siyuan Huang, Xiaopei Zhu, Fuchun Sun, Bo Zhang, Xiaolin Hu*, “Adversarial texture for fooling person detectors in the physical world”, Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Orleans, Louisian, June 19-24, 2022, pp. 13307-13316. (Oral, acceptance rate4.2%)
[7] Xiaopei Zhu, Zhanhao Hu, Siyuan Huang, Jianmin Li, Xiaolin Hu*, “Infrared invisible clothing: hiding from infrared detectors at multiple angles in real world”, Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Orleans, Louisian, June 19-24, 2022. (Oral, acceptance rate4.2%)
[8] Fangzhou Liao, Ming Liang, Zhe Li, Xiaolin Hu*, Sen Song*, “Evaluate the malignancy of pulmonary nodules using the 3-D deep leaky noisy-or network,” IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 11, pp. 3484-3495, 2019.
[9] Qingtian Zhang, Xiaolin Hu*, Bo Hong, Bo Zhang, “A hierarchical sparse coding model predicts acoustic feature encoding in both auditory midbrain and cortex,” PLOS Computational Biology, 2019.
[10] Fangzhou Liao, Ming Liang, Yinpeng Dong, Tianyu Pang, Xiaolin Hu*, Jun Zhu, “Defense against adversarial attacks using high-level representation guided denoiser,” Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018, pp. 1778-1787.
Contact Information
Email: xlhu@tsinghua.edu.cn
Office: FIT Building 1-508, Tsinghua University, Haidian District, Beijing, China
Phone: +86-10-62799932
Webpage: www.xlhu.cn
