Youwei Liang

I am a PhD student in the Department of Electrical and Computer Engineering at the University of California, San Diego. My PhD advisor is Prof. Pengtao Xie. Before coming to UCSD, I spent some good time working as a research intern in the Visual Computing Center at Tencent AI Lab, supervised by Dr. Yibing Song. Prior to that, I was an undergraduate student studying Information and Computing Science at SCAU, where I had the fortune to have Prof. Dong Huang being my advisor.


  • [06/2022] I started a summer research internship at Meta FAIR Labs in its Menlo Park office.
  • [01/2022] One paper was accepted as a spotlight at ICLR 2022.
  • [12/2021] I co-organized an NeurIPS 2021 Workshop: Self-Supervised Learning - Theory and Practice.

Research Interests

I am broadly interested in machine learning, especially unsupervised/self-supervised learning such as generative models (e.g., GAN and VAE), contrastive/predictive learning (e.g., MoCo, BYOL, and CARE), and optimization.

I am currently working on accelerating the training and inference of deep learning models, with an emphasis on Vision Transformers. My previous projects span various aspects in machine learning, from multi-view clustering to theories of the Lipschitz constants and adversarial robustness of CNN, to self-supervised learning. If you are interested in my works, please feel free to contact me.

Selected Publications

Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations
Youwei Liang, Chongjian GE, Zhan Tong, Yibing Song, Jue Wang, and Pengtao Xie
International Conference on Learning Representations (ICLR 2022 Spotlight). [OpenReview] [Code]

Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning
Chongjian Ge, Youwei Liang, Yibing Song, Jianbo Jiao, Jue Wang, and Ping Luo
Advances in Neural Information Processing Systems (NeurIPS 2021). [arXiv] [Code]

Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering
Youwei Liang, Dong Huang, and Chang-Dong Wang
IEEE International Conference on Data Mining (ICDM 2019). [PDF] [Code] [Slides] [YouTube]

More Publications

Professional Services


  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • ICML 2022, NeurIPS 2022