Xiaolin Hu
Associate Professor
Email: xlhu@tsinghua.edu.cn
URL: www.xlhu.cn
Tel: +86-10-62799932
Education
2004-2007 The Chinese University of Hong Kong, Hong Kong, China, PhD
2001-2004 Wuhan University of Technology, Wuhan, China, Master
1997-2001 Wuhan University of Technology, Wuhan, China, Bachelor
Teaching
00240332 Introduction to Deep Learning
00240332 Neural and Cognitive Computation
80240743 Deep Learning
40240982 Deep Learning and Financial Data Analysis
Research Areas
Artificial neural networks, computational neuroscience
Research Status
Currently I have two major interests. First, adversarial attack and defense of deep learning models. We are trying to craft adversarial examples in both the digital world and physical world. In this way, we expose the vulnerability and risk of deep learning models. We're also looking for ways to get more robust deep learning models. Second, brain-inspired computational models. We develop new models to circumvent the limitations that current deep learning models are facing including the above stated vulnerability. Towards this goal, we are collaborating with neuroscientists to unravel the neural wiring diagram of the mouse brain and simulate different physiological functions of animal brains. I have published more than 100 papers in international journals and conferences, cited in Google Scholar by more than 20000+ times.
Recent Publications
1. Xiao Li, Hang Chen, Xiaolin Hu, “On the importance of backbone to the adversarial robustness of object detectors,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 2387-2398, 2025.
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. Xiao Li, Yiming Zhu, Yifan Huang, Wei Zhang, Yingzhe He, Jie Shi, Xiaolin Hu, “PBCAT: patch-based composite adversarial training against physically realizable attacks on object detection,” Proc. of the International Conference on Computer Vision (ICCV), Honolulu, Hawaii, Oct 19th-23rd, 2025.
4. Han Liu, Peng Cui, Bingning Wang, Weipeng Chen, Yupeng Zhang, Jun Zhu, Xiaolin Hu, “Improving accuracy and calibration via differentiated deep mutual learning,” Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Nashville TN, June 11th-15th, 2025.
5. Chongkai Yu, Ting Liu, Li Anqi, Xiaochao Qu, Chengjing Wu, Luoqi Liu, Xiaolin Hu, “SAM-REF: introducing image-prompt synergy during interaction for detail enhancement in the segment anything model,” Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Nashville TN, June 11th-15th, 2025.
6. Kai Li, Wendi Sang, Chang Zeng, Runxuan Yang, Guo Chen, Xiaolin Hu, “SonicSim: a customizable simulation platform for speech processing in moving sound source scenarios,” Proc. of the 13th International Conference on Learning Representations (ICLR), Singapore, Apr 24th-28th, 2025.
7. Mohan Xu, Kai Li, Guo Chen, Xiaolin Hu, “TIGER: time-frequency interleaved gain extraction and reconstruction for efficient speech separation”, Proc. of the 13th International Conference on Learning Representations (ICLR), Singapore, Apr 24th-28th, 2025.
8. Hang Chen, Chufeng Tang, Xiao Li, Xiaolin Hu, “Efficient neuron segmentation in electron microscopy by affinity-guided queries,” Proc. of the 13th International Conference on Learning Representations (ICLR), Singapore, Apr 24th-28th, 2025.
9. Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yining Liu, Yingzhe He, Jie Shi, Xiaolin Hu, “ADBM: adversarial diffusion bridge model for reliable adversarial purification,” Proc. of the 13th International Conference on Learning Representations (ICLR), Singapore, Apr 24th-28th, 2025.
10. Zhi Cheng, Zhanhao Hu, Yuqiu Liu, Hang Su, Xiaolin Hu, “Full-distance evasion of pedestrian detectors in the physical world,” Advances in Neural Information Processing (NeurIPS), Vancouver, Canada, Dec 10th-15th, 2024.
