Li Xiaoli

Li Xiaoli

SUTD

Publications

You can also find my articles on my Google Scholar profile.

Selected Journal Papers

  1. Aye Phyu Phyu Aung, Xinrun Wang, Ruiyu Wang, Hau Chan, Bo An, Xiaoli Li, J. Senthilnath, “Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models”, IEEE Transactions on Image Processing, 2025.
  2. Xue Geng, Zhe Wang, Chunyun Chen, Qing Xu, Kaixin Xu, Chao Jin, Manas Gupta, Xulei Yang; Chen, Zhenghua Chen, Mohamed Sabry Aly, Jie Lin, Min Wu, Xiaoli Li, “From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks”, IEEE Transactions on Neural Networks and Learning Systems, 2024.
  3. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, “Label-efficient Time Series Representation Learning: A Review”, IEEE Transactions on Artificial Intelligence (TAI), 2024.
  4. Yucheng Wang, Yuecong Xu, Jianfei Yang, Min Wu, Xiaoli Li, Lihua Xie, Zhenghua Chen, “SEA++: Multi-Graph-based High-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
  5. Keyu Wu, Shengkai Chen, Min Wu, Shili Xiang, Ruibing Jin, Yuecong Xu, Xiaoli Li, Zhenghua Chen, “Reinforced Reweighting for Self-supervised Partial Domain Adaptation”, IEEE Transactions on Artificial Intelligence, 2024.
  6. Qing Xu, Keyu Wu, Min Wu, Kezhi Mao, Xiaoli Li, Zhenghua Chen, “Reinforced knowledge distillation for time series regression”, IEEE Transactions on Artificial Intelligence (TAI), 2024.
  7. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan, “Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  8. Zhenghua Chen, Min Wu, Alvin Chan, Xiaoli Li, Yew-Soon Ong, “A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges”, IEEE Computational Intelligence Magazine, 2023.
  9. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, “Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation”, IEEE in Transactions on Neural Systems & Rehabilitation Engineering, 2023.
  10. Yucheng Wang, Min Wu, Ruibing Jin, Xiaoli Li, Lihua Xie, Zhenghua Chen, “Local-Global Correlation Fusion based Graph Neural Network for Remaining Useful Life Prediction”, IEEE Transactions on Neural Networks and Learning Systems, 2023.
  11. Mohamed Ragab Mohamed Adam, Emadeldeen Eldele, Wee Ling Tan, Foo Chuan Sheng, Chen Zhenghua, Wu Min, Kwoh Chee-Keong, Xiaoli Li, “ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data”, ACM Transactions on Knowledge Discovery from Data (TKDD), 2023.
  12. Jin Ruibing, Zhou Duo, Wu Min, Xiaoli Li, Chen Zhenghua, “An adaptive and dynamical neural network for machine remaining useful life prediction”, IEEE Transactions on Industrial Informatics, 2023.
  13. Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh and Xiaoli Li, “Self-supervised Autoregressive Domain Adaptation for Time Series Data”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
  14. Devki Nandan Jha, Zhenghua Chen, Shudong Liu, Min Wu, Jiahan Zhang, Graham Morgan, Rajiv Ranjan, and Xiaoli Li, “A hybrid accuracy- and energy-aware human activity recognition model in IoT environment”, IEEE Transactions on Sustainable Computing, 2022.
  15. Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee-Keong Kwoh, Jinmiao Chen, Jiawei Luo and Xiaoli Li, “Pre-training Graph Neural Networks for Link Prediction in Biomedical Networks”, Bioinformatics, 2022.

Selected Conference Papers

  1. Yao Xiao, Hai Ye, Linyao Chen, Hwee Tou Ng, Lidong Bing, Xiaoli Li, Roy Ka-Wei Lee, “Finding the Sweet Spot: Preference Data Construction for Scaling Preference Optimization”, ACL 2025.
  2. Jiaxuan Zhang, Emadeldeen Eldele, Fuyuan CAO, Yang Wang, Xiaoli Li, Jiye Liang, “Counterfactual Contrastive Learning with Normalizing Flows for Robust Treatment Effect Estimation”, ICML 2025.
  3. Peiliang Gong, Mohamed Ragab, Min Wu, Zhenghua Chen, Yongyi Su, Xiaoli Li, Daoqiang Zhang, “Augmented Contrastive Clustering with Uncertainty-Aware Prototyping for Time Series Test Time Adaptation”, KDD 2025.
  4. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Xiaoli Li, “TSLANet: Rethinking Transformers for Time Series Representation Learning”, ICML 2024.
  5. Qing Xu, Min Wu, Xiaoli Li, Kezhi Mao, Zhenghua Chen, “Reinforced Cross-Domain Knowledge Distillation on Time Series Data”, NeurIPS 2024.
  6. Yucheng Wang, Yuecong Xu, Zhenghua Chen, Min Wu, Xiaoli Li, “SEnsor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation”, AAAI 2023.
  7. Wang Jing, Aixin Sun, Hao Zhang and Xiaoli Li, “MS-DETR: Natural Language Video Localization with Sampling Moment-Moment Interaction”, ACL 2023.
  8. Aye Phyu Phyu Aung, Xinrun Wang, Runsheng Yu, Bo An, Senthilnath Jayavelu, Xiaoli Li, “DO-GAN: A double oracle framework for generative adversarial networks”, CVPR 2022.
  9. Keyu Wu, Wu Min, Chen Zhenghua, Xu Yuecong and Xiaoli Li, “Generalizing Reinforcement Learning through Fusing Self-Supervised Learning into Intrinsic Motivation”, AAAI 2022.
  10. Keyu Wu, Min Wu, Jianfei Yang, Zhenghua Chen, Zhengguo Li, and Xiaoli Li, “Deep Reinforcement Learning Boosted Partial Domain Adaptation”, IJCAI 2021.
  11. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li and Cuntai Guan, “Time-Series Representation Learning via Temporal and Contextual Contrasting”, IJCAI 2021.