Skip to main content
Skip to main menu


Sheng Li

Blurred image of the arch used as background for stylistic purposes.
Assistant Professor, Department of Computer Science

PhD in CE, Northeastern, 2017

MSc in CS, NUPT, 2012;

B.S. in CS, NUPT, 2010.

Research Interests:

Trustworthy Representation Learning (e.g., Robustness, Fairness, Causality, Transferability);

Visual Intelligence

User Modeling

Natural Language Understanding


Biomedical Informatics.

Selected Publications:
  1. Rahil Taujale*, Zhongliang Zhou*, Wayland Yeung, Kelley Moremen, Sheng Li, and Natarajan Kannan. Mapping the glycosyltransferase fold landscape using interpretable deep learning. Nature Communications, 2021. (* indicates equal contribution)
  2. Heng-Shiou Sheu, Zhixuan Chu, Daiqing Qi, and Sheng Li. Knowledge-Guided Article Embedding Refinement for Session-based News Recommendation. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021.
  3. Ronghang Zhu, Xiaodong Jiang, Jiasen Lu, and Sheng Li. Cross-Domain Graph Convolutions for Adversarial Unsupervised Domain Adaptation. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021.
  4. Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, and Aidong Zhang. A Survey on Causal Inference. ACM Trans. Knowledge Discovery from Data (TKDD), 2021.
  5. Xiaodong Jiang, Ronghang Zhu, Pengsheng Ji, and Sheng Li. Co-embedding of Nodes and Edges with Graph Neural Networks. IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI), 2020. [Code]
  6. Rahil Taujale, Aarya Venkat, Liang-Chin Huang, Zhongliang Zhou, Wayland Yeung, Khaled M Rasheed, Sheng Li, Arthur S Edison, Kelley W Moremen, Natarajan Kannan. Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases. eLife, 2020.
  7. Jiahuan Ren, Zhao Zhang, Sheng Li, Yang Wang, Guangcan Liu, Shuicheng Yan, and Meng Wang. Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space. IEEE Trans. Image Processing (T-IP), 2020.
  8. Liang‑Chin Huang, Wayland Yeung, Ye Wang, Huimin Cheng, Aarya Venkat, Sheng Li, Ping Ma, Khaled Rasheed, and Natarajan Kannan. Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction. BMC Bioinformatics, 2020.
  9. Sheng Li*, Zhiqiang Tao*, Kang Li, Yun Fu. Visual to Text: Survey of Image and Video Captioning. IEEE Trans. Emerging Topics in Computational Intelligence (T-ETCI), 2019. (* indicates equal contribution)
  10. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, and Yun Fu. Marginalized Multi-View Ensemble Clustering. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2019.
Of note:

Openings: I am continuously looking for highly-motivated Ph.D. students to work on machine learning, computer vision, and causal inference. Please send me your CV if interested.

Support us

We appreciate your financial support. Your gift is important to us and helps support critical opportunities for students and faculty alike, including lectures, travel support, and any number of educational events that augment the classroom experience. Click here to learn more about giving.

Every dollar given has a direct impact upon our students and faculty.