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Associate Professor, Department of Computer Science and Technology, Tsinghua University
PI，IDG/McGovern Institute, Tsinghua University
Lab address：FIT Building 1-508, Tsinghua University
Lab phone：+86-10-6279 9932
Email: xlhu@tsinghua.edu.cn
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[Research Focus]
My main research interest lies in the intersection of deep learning and neuroscience. On one hand, inspired by the brain, I want to propose new deep learning models to circumvent the difficulties that current deep learning models are facing. On the other hand, using deep learning techniques, I try to unravel the secrete of the brain about how it processes sensory information. My lab also conducts research on various applications of deep learning such as traffic sign detection, face detection, image segmentation, medical image analysis, etc. Recently, we started a project about music generation, aiming to automatically generate elements of music including lyric, melody and chords.
[Education & Experience]
2013.12 - Department of Computer Science and Technology, Tsinghua University, Associate Professor
2009.09 - 2013.11 Department of Computer Science and Technology, Tsinghua University, Assistant Professor
2007.09 - 2009.08 Department of Computer Science and Technology, Tsinghua University, Postdoc
2004.08 - 2007.07 The Chinese University of Hong Kong, Ph.D.
2001.09 - 2004.06 Wuhan University of Technology, M.S.
1997.09 - 2001.06 Wuhan University of Technology, B.S.
[Selected Publicaitons]
- 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 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018.
- Yulong Wang, Hang Su, Bo Zhang, Xiaolin Hu*, “Interpret neural networks by identifying critical data routing paths,” Proc. of the 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018.
- Wentao Liu, Jie Chen, Cheng Li, Chen Qian, Xiao Chu, Xiaolin Hu*, “A cascaded inception of inception network with attention modulated feature fusion for human pose estimation,” The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), New Orleans, USA, Feb 14-19, 2018.
- Jianfeng Wang, Xiaolin Hu*, “Gated recurrent convolution neural network for OCR,” Advancies in Neural Information Processing (NIPS), Long Beach, USA, Dec. 4-9, 2017.
- Ming Liang, Xiaolin Hu*, Bo Zhang, “Convolutional neural networks with intra-layer recurrent connections for scene labeling,” Advances in Neural Information Processing (NIPS), Montréal, Canada, Dec. 7-12, 2015.
- Ming Liang, Xiaolin Hu*, “Recurrent convolutional neural network for object recognition,” Proc. of the 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, USA, June 7-12, 2015, pp. 3367-3375.
- 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.
- Chengxu Zhuang, Yulong Wang, Daniel Yamins, Xiaolin Hu*, “Deep learning predicts correlation between a functional signature of higher visual areas and sparse firing of neurons,” Frontiers in Computational Neuroscience, 2017.