Education
- Ph.D. in Electronic Engineering (with Distinction), Tsinghua University, China, 2018–2023
- B.E. in Electronic Engineering, Tsinghua University, China, 2014–2018
Professional Experience
- Assistant Professor, Department of Biomedical Engineering, National University of Singapore, Singapore, 2026–Present
- Postdoctoral Researcher, Department of Engineering Science, University of Oxford, UK, 2023–2026
Research Interests
My research advances knowledge-centric artificial intelligence (AI) for healthcare by developing methods that integrate medical knowledge, multimodal health data, and emerging AI paradigms, including foundation models, AI agents, and knowledge graphs. By leveraging AI to uncover actionable insights into health and aging, my research aims to enable trustworthy decision support across personalized health, population health, and mobile and wearable health, benefiting individuals, communities, and healthcare systems.
Selected Awards & Honours
- Junior Research Fellow, Kellogg College, University of Oxford, 2025
- Best Visual for Poster Award, Nature Forum: 3rd Healthy Longevity Symposium, 2025
- NeurIPS Top Reviewer Award, 2025
- ACM KDD Outstanding Reviewer Award, 2025
- Outstanding Doctoral Dissertation Award, Tsinghua University, 2023
- Outstanding Freshman Scholarship, Tsinghua University, 2014
Selected Publications
- C. Li*, Yu Liu*, T. Denison, and T. Zhu. “BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals.” International Conference on Learning Representations (ICLR),2026. Oral presentation. *Equal contribution.
- Z. Shen, Yu Liu, X. Fu, and Q. Yao. “DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction.” Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026.
- Yu Liu, W. Tao, T. Xia, S. Knight, and T. Zhu. “SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Models.” Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.
- M. Gögl, Yu Liu, C. Yau, P. Watkinson, and T. Zhu. “DoseSurv: Predicting Personalized Survival Outcomes under Continuous-Valued Treatments.” Advances in Neural Information Processing Systems (NeurIPS),2025.
- Z. Cai, Yu Liu†, Z. Luo, and T. Zhu. “ProtoEHR: Hierarchical Prototype Learning for EHR-Based Healthcare Predictions.” Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2025. †Corresponding author.
- J. Laiti, Yu Liu, P. J. Dunne, E. Byrne, and T. Zhu. “Real-World Classification of Student Stress and Fatigue Using Wearable PPG Recordings.” IEEE Transactions on Affective Computing (TAC), 2025.
- M. Zhu, Yu Liu, Z. Luo, and T. Zhu. “Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction.” npj Digital Medicine , 2025.
- Yu Liu, X. Zhang, J. Ding, Y. Xi, and Y. Li. “Knowledge-Infused Contrastive Learning for Urban Imagery-Based Socioeconomic Prediction.” Proceedings of the ACM Web Conference (WWW), 2023.
- Yu Liu, J. Ding, Y. Fu, and Y. Li. “UrbanKG: An Urban Knowledge Graph System.” ACM Transactions on Intelligent Systems and Technology (TIST), 2023.
- Yu Liu, Q. Yao, and Y. Li. “Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases.” Proceedings of the ACM Web Conference (WWW), 2020.