Shuang Li

Name: Li Shuang
Discipline: Computer Science and Technology
Title: Associate Professor, Special Researcher, Doctoral Supervisor
Contact number:
E-mail: shuangli@bit.edu.cn
Address: Beijing Polytechnic University Center Teaching Building Personal Information
Dr. Li Shuang is an Associate professor, special researcher and doctoral supervisor of the School of Computer Science. He received his bachelor of Engineering degree from Northeastern University in 2012 and doctorate degree from the Department of Automation of Tsinghua University in 2018. From 2015 to 2016, he had an academic visit in the School of Computer Science of Cornell University in the United States. From 2016 to 2017, he worked as an intern in Microsoft Research Asia. His research interests include machine learning, deep learning and transfer learning. His research results have been published in the international top journals IEEE TPAMI, TIP, TKDE,TCYB TNNLS and other top conferences NeurIPS, ICLR, CVPR, AAAI, ACM MM and nearly 50 papers, including 31 CCF-A class papers (1 work / 28 correspondence). It has been widely concerned by academia and industry at home and abroad. In the field of scientific research, Dr. Li Shuang has worked with Cornell University, UC Berkeley, University of Edinburgh, National University of Singapore, Nanyang Technological University of Singapore, Tsinghua University and other top universities at home and abroad. Well-known research institutions such as Microsoft Research Asia (MSRA) and Alidama Institute have long-term exchanges and cooperation to ensure the cutting-edge and practical scientific research.
Each year, one doctoral student, two to three master's students and a number of undergraduate students committed to academic research are enrolled to research and publish high-level papers together. Preference will be given to students with ACM programming Competition, programming competition, mathematical Contest in Modeling, or other scientific research background. Laboratory teachers and students harmonious relationship, common growth, welcome to contact and exchange discussion.
For more information please visit shuangli.xyz

Research Direction
1. Transfer Learning/Domain Adaptation algorithm and Application
2, Machine learning, deep learning, reinforcement learning algorithms and applications
3. Application of computer vision in unmanned driving, intelligent medical treatment and industrial quality inspection

Personal Information
Dr. Li Shuang is an Associate professor, special researcher and doctoral supervisor of the School of Computer Science. He received his bachelor of Engineering degree from Northeastern University in 2012 and doctorate degree from the Department of Automation of Tsinghua University in 2018. From 2015 to 2016, he had an academic visit in the School of Computer Science of Cornell University in the United States. From 2016 to 2017, he worked as an intern in Microsoft Research Asia. His research interests include machine learning, deep learning and transfer learning. His research results have been published in the international top journals IEEE TPAMI, TIP, TKDE,TCYB TNNLS and other top conferences NeurIPS, ICLR, CVPR, AAAI, ACM MM and nearly 50 papers, including 31 CCF-A class papers (1 work / 28 correspondence). It has been widely concerned by academia and industry at home and abroad. In the field of scientific research, Dr. Li Shuang has worked with Cornell University, UC Berkeley, University of Edinburgh, National University of Singapore, Nanyang Technological University of Singapore, Tsinghua University and other top universities at home and abroad. Well-known research institutions such as Microsoft Research Asia (MSRA) and Alidama Institute have long-term exchanges and cooperation to ensure the cutting-edge and practical scientific research.
Each year, one doctoral student, two to three master's students and a number of undergraduate students committed to academic research are enrolled to research and publish high-level papers together. Preference will be given to students with ACM programming Competition, programming competition, mathematical Contest in Modeling, or other scientific research background. Laboratory teachers and students harmonious relationship, common growth, welcome to contact and exchange discussion.
For more information please visit shuangli.xyz

Personal Information
Dr. Li Shuang is an Associate professor, special researcher and doctoral supervisor of the School of Computer Science. He received his bachelor of Engineering degree from Northeastern University in 2012 and doctorate degree from the Department of Automation of Tsinghua University in 2018. From 2015 to 2016, he had an academic visit in the School of Computer Science of Cornell University in the United States. From 2016 to 2017, he worked as an intern in Microsoft Research Asia. His research interests include machine learning, deep learning and transfer learning. His research results have been published in the international top journals IEEE TPAMI, TIP, TKDE,TCYB TNNLS and other top conferences NeurIPS, ICLR, CVPR, AAAI, ACM MM and nearly 50 papers, including 31 CCF-A class papers (1 work / 28 correspondence). It has been widely concerned by academia and industry at home and abroad. In the field of scientific research, Dr. Li Shuang has worked with Cornell University, UC Berkeley, University of Edinburgh, National University of Singapore, Nanyang Technological University of Singapore, Tsinghua University and other top universities at home and abroad. Well-known research institutions such as Microsoft Research Asia (MSRA) and Alidama Institute have long-term exchanges and cooperation to ensure the cutting-edge and practical scientific research.
Each year, one doctoral student, two to three master's students and a number of undergraduate students committed to academic research are enrolled to research and publish high-level papers together. Preference will be given to students with ACM programming Competition, programming competition, mathematical Contest in Modeling, or other scientific research background. Laboratory teachers and students harmonious relationship, common growth, welcome to contact and exchange discussion.
For more information please visit shuangli.xyz

代表性学术成果
[1] Shuang Li, Chi Harold Liu, Qiuxia Lin, Qi Wen, Limin Su, Gao Huang and Zhengming Ding. “Deep Residual Correction Network for Partial Domain Adaptation”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021, [IF: 24.314], SCI 1区, CCF-A.
[2] Shuang Li, Binhui Xie, Qiuxia Lin, Chi Harold Liu, Gao Huang and Guoren Wang. “Generalized Domain Conditioned Adaptation Network”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022, [IF: 24.314], SCI 1区, CCF-A.
[3] Binhui Xie, Shuang Li*, Mingjia Li, Chi Harold Liu, Gao Huang and Guoren Wang. “SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, [IF: 24.314], SCI 1区, CCF-A.
[4] Shuang Li, Wenxuan Ma, Jinming Zhang, Chi Harold Liu, Jian Liang, Guoren Wang. “Meta-reweighted Regularization for Unsupervised Domain Adaptation”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, [IF: 9.235], SCI 1区, CCF-A.
[5] Shuang Li, Shugang Li, Mixue Xie, Kaixiong Gong, Jianxin Zhao, Chi Harold Liu, Guoren Wang. “End-to-End Transferable Anomaly Detection via Multi-spectral Cross-domain Representation Alignment”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, [IF: 9.235], SCI 1区, CCF-A.
[6] Binhui Xie, Shuang Li*, Fangrui Lv, Chi Harold Liu, Guoren Wang, Dapeng Wu. “A Collaborative Alignment Framework of Transferable Knowledge Extraction for Unsupervised Domain Adaptation”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022, [IF: 9.235], SCI 1区, CCF-A.
[7] Shuang Li, Shiji Song, Gao Huang, Zhengming Ding, Cheng Wu, “Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation”, IEEE Transactions on Image Processing (TIP) 27(9): 4260-4273 (2018). [IF: 9.34], SCI 1区, CCF-A.
[8] Yiming Chen , Shiji Song , Shuang Li*, Cheng Wu. “A Graph Embedding Framework for Maximum Mean Discrepancy Based Domain Adaptation Algorithms”. IEEE Transactions on Image Processing (TIP) 29:199-213 (2020), [IF: 11.041], SCI 1区, CCF-A.
[9] Shuang Li, Kaixiong Gong, Binhui Xie, Chi Harold Liu, Weipeng Cao, Song Tian. “Critical Classes and Samples Discovering for Partial Domain Adaptation”. IEEE Transactions on Cybernetics (TCYB), 2022. [IF: 19.118], SCI 1区.
[10] Shuang Li, Chi Harold Liu, Limin Su, Binhui Xie, Zhengming Ding, C. L. Philip Chen, Dapeng Wu. “Discriminative Transfer Feature and Label Consistency for Cross-Domain Image Classification”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 31(11): 4842-4856 (2020), SCI 1区.
[11] Ying Zhao, Shuang Li*, Rui Zhang, Chi Harold Liu, Weipeng Cao, Xizhao Wang, Song Tian. “Semantic Correlation Transfer for Heterogeneous Domain Adaptation”. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022, [IF: 14.255], SCI 1区.
[12] Zhenjie Yu, Shuang Li*, Yirui Shen, Chi Harold Liu, Shuigen Wang. "On the Difficulty of Unpaired Infrared-to-Visible Video Translation: Fine-Grained Content-Rich Patches Transfer", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023, CCF-A.
[13] Mixue Xie, Shuang Li*, Rui Zhang, Chi Harold Liu. "Dirichlet-based Uncertainty Calibration for Active Domain Adaptation", International Conference on Learning Representations (ICLR), 2023, (Spotlight).
[14] Mingjia Li, Binhui Xie, Shuang Li*, Chi Harold Liu, Xinjing Cheng. "VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions", AAAI Conference on Artificial Intelligence (AAAI), 2023, (Oral Presentation), CCF-A.
[15] Kaixiong Gong, Shuang Li*, Shugang Li, Rui Zhang, Chi Harold Liu, Qiang Chen. "Improving Transferability for Domain Adaptive Detection Transformers", ACM Multimedia (ACM MM), 2022, CCF-A.
[16] Zhenjie Yu, Kai Chen, Shuang Li*, Bingfeng Han, Chi Harold Liu, Shuigen Wang. "ROMA: Cross-Domain Region Similarity Matching for Unpaired Nighttime Infrared to Daytime Visible Video Translation", ACM Multimedia (ACM MM), 2022, CCF-A.
[17] Wenxuan Ma, Jinming Zhang, Shuang Li*, Chi Harold Liu, Yulin Wang, Wei Li. "Making The Best of Both Worlds: A Domain-Oriented Transformer for Unsupervised Domain Adaptation", ACM Multimedia (ACM MM), 2022, CCF-A.
[18] Fangrui Lv, Jian Liang, Shuang Li*, Bin Zang, Chi Harold Liu, Ziteng Wang, Di Liu. "Causality Inspired Representation Learning for Domain Generalization", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022, (Oral Presentation), CCF-A.
[19] Binhui Xie, Longhui Yuan, Shuang Li*, Chi Harold Liu, Xinjing Cheng. "Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022, (Oral Presentation), CCF-A.
[20] Binhui Xie, Longhui Yuan, Shuang Li*, Chi Harold Liu, Xinjing Cheng, Guoren Wang. “Active Learning for Domain Adaptation: An Energy-based Approach”, AAAI Conference on Artificial Intelligence (AAAI), 2022, CCF-A.
[21] Fangrui Lv, Jian Liang, Kaixiong Gong, Shuang Li*, Chi Harold Liu, Han Li, Di Liu, Guoren Wang. "Pareto Domain Adaptation", Neural Information Processing Systems (NeurIPS), 2021, CCF-A.
[22] Shuang Li, Mixue Xie, Fangrui Lv, Chi Harold Liu, Jian Liang, Chen Qin, Wei Li. "Semantic Concentration for Domain Adaptation", International Conference on Computer Vision (ICCV), 2021, CCF-A.
[23] Shuang Li, Bingfeng Han, Zhenjie Yu, Chi Harold Liu, Kai Chen, Shuigen Wang. "I2V-GAN: Unpaired Infrared-to-Visible Video Translation", ACM Multimedia (ACM MM), 2021, CCF-A.
[24] Qi Wen, Shuang Li, Bingfeng Han, Yi Yuan. "ZiGAN: Fine-grained Chinese Calligraphy Font Generation via a Few-shot Style Transfer Approach", ACM Multimedia (ACM MM), 2021, CCF-A.
[25] Shuang Li, Mixue Xie, Kaixiong Gong, Chi Harold Liu, Yulin Wang, Wei Li. "Transferable Semantic Augmentation for Domain Adaptation", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, (Oral Presentation), CCF-A.
[26] Yan Xia, Yusheng Xu, Shuang Li, Rui Wang, Juan Du, Uwe Stilla. "SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, (Oral Presentation), CCF-A.
[27] Shuang Li, Kaixiong Gong, Chi Harold Liu, Yulin Wang, Feng Qiao, Xinjing Cheng. "MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, CCF-A.
[28] Shuang Li, Jinming Zhang, Wenxuan Ma, Chi Harold Liu, Wei Li. "Dynamic Domain Adaptation for Efficient Inference", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, CCF-A.
[29] Shuang Li, Fangrui Lv, Binhui Xie, Chi Harold Liu, Jian Liang, Chen Qin. “Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation”, AAAI Conference on Artificial Intelligence (AAAI), 2021, CCF-A.
[30] Shuang Li, Binhui Xie, Jiashu Wu, Ying Zhao, Chi Harold Liu, Zhengming Ding. "Simultaneous Semantic Alignment Network for Heterogeneous Domain Adaptation", ACM Multimedia (ACM MM) 2020: 3866-3874, CCF-A.
[31] Shuang Li, Chi Harold Liu, Qiuxia Lin, Binhui Xie, Zhengming Ding, Gao Huang, Jian Tang. “Domain Conditioned Adaptation Network”, AAAI Conference on Artificial Intelligence (AAAI), 2020, CCF-A.
[32] Shuang Li, Chi Harold Liu, Binhui Xie, Limin Su, Zhengming Ding, Gao Huang. “Joint Adversarial Domain Adaptation”, ACM Multimedia (ACM MM), 2019: 729-737, CCF-A.
所获奖励
1. 教育部自然科学一等奖（2023），排名4/8
2. 山东省烟台开发区创新创业领军人才（2021）
3. 北京市优秀毕业生（2018）
4. 清华大学自动化系优秀毕业生（2018）