Hi! I am Siteng Huang (黄思腾 in Chinese). I am a joint Ph.D. student of Zhejiang University and Westlake University, advised by Dr. Donglin Wang. And I am a member of Machine Intelligence Laboratory (MiLAB) in Westlake University, where I do my research work on machine learning and robot learning. Currently, I am also a research intern at DAMO Academy, Alibaba Group. I received my B.Eng. Degree from School of Computer Science, Wuhan University in 2019.
I am interested in technologies that allow machines and robots to learn like humans. In particular, I am committed to giving robots the ability to understand the world and learn from previous experiences, so that they can complete new tasks, acquire new skills or adapt to new environments rapidly with fewer samples through learning algorithms. Currently, my areas of interest include meta-learning, multi-task learning, and transfer learning on few/zero-shot learning tasks. I am also interested in deep learning, computer vision, and multimodal machine learning.
- [July 4, 2022] One paper got accepted for ECCV 2022.
- [March 14, 2022] Started as a research intern at DAMO Academy, Alibaba Group.
- [January 22, 2022] One paper got accepted for ICASSP 2022.
- [December 21, 2021] DSANet has been cited 50 times according to Google Scholar!
- [April 21, 2021] One paper got accepted for ICMR 2021.
- [March 4, 2021] One paper got accepted for CVPR 2021.
- [December 2, 2020] One paper about few-shot recognition got accepted for AAAI 2021. Congratulations to all collaborators!
Service: Always open to paper review, talk and organizing opportunities. Feel free to reach out to me if you are interested.
Hiring: We are looking for postdoctors, research assistants and visiting students for MiLAB (currently only for Chinese). More information about requirements can be found here, and if you are still in school, being a visiting student is also welcome. Please send email to
mi_lab [at] westlake.edu.cn with your CV if you are interested. Specially, if you are interested in my research direction and would like to be my collaborator after coming, please specify in the email and also send a copy to me.
- Siteng Huang, Qiyao Wei and Donglin Wang, "Reference-Limited Compositional Zero-Shot Learning". arXiv preprint arXiv:2208.10046. [pdf]
Siteng Huang, Donglin Wang, Xuehan Wu, Ao Tang, "DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting". In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019). [project page] [pdf] [bib] [code] [poster] [slide]
Siteng Huang, Min Zhang, Yachen Kang, Donglin Wang, "Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition". In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021). [project page] [arXiv] [bib] [code] [poster] [slide]
Zhengyu Chen, Jixie Ge, Heshen Zhan, Siteng Huang, Donglin Wang, "Pareto Self-Supervised Training for Few-Shot Learning". In Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021). [arXiv]
Zifeng Zhuang, Xintao Xiang, Siteng Huang, Donglin Wang, "HINFShot: A Challenge Dataset for Few-Shot Node Classification in Heterogeneous Information Network". In Proceedings of the 2021 International Conference on Multimedia Retrieval (ICMR 2021). [pdf]
Min Zhang, Siteng Huang, Donglin Wang, "Domain Generalized Few-shot Image Classification via Meta Regularization Network". In Proceedings of the 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022). [pdf]
Min Zhang, Siteng Huang, Wenbin Li, Donglin Wang, "Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation". In Proceedings of the European Conference on Computer Vision 2022 (ECCV 2022). [arXiv]