Email: yu_liu [AT] nus.edu.sg
Office: 06-01A, E7 Building, NUS, Singapore 119276
I am an Assistant Professor in the Department of Biomedical Engineering, National University of Singapore (NUS). Before joining NUS, I was a Postdoctoral Researcher in the Department of Engineering Science, University of Oxford, from 2023 to 2025, and a Junior Research Fellow at Kellogg College in 2025. I received my Ph.D. degree with Distinction in 2023 and my B.Eng. degree in 2018, both from the Department of Electronic Engineering, Tsinghua University.
My research advances knowledge-centric artificial intelligence (AI) for healthcare by developing methods grounded in medical knowledge, with the ultimate goal of enabling trustworthy decision support across personalized, population, and mobile health to benefit individuals, communities, and healthcare systems.
I am actively looking for self-motivated Ph.D. students, postdoctoral researchers, research assistants, and visiting students to join my group. Prospective applicants and NUS students interested in research opportunities are welcome to email me with your CV.
Potential Scholarship Opportunities:
- President's Graduate Fellowship (PGF)
- AI Singapore Scholarship
- NUS Research Scholarship
- NUS Industry-Relevant PhD Scholarship (NUS-IRP)
- A*STAR Graduate Scholarship
- A*STAR Computing and Information Science (ACIS) Scholarship
- Lee Kuan Yew Scholarship
- NUS ASEAN Research Scholarship
- Commonwealth Scholarship
Research Areas
-
Knowledge Synergy for Medical Foundation Models:
Integrating clinical knowledge into foundation models to improve their reliability, generalizability, and utility in healthcare. -
Trustworthy Agentic AI for Clinical Decision Support:
Building reliable and knowledge-guided AI agents that support transparent, safe, and clinically meaningful decision-making. -
Multimodal Learning for Healthcare Applications:
Developing multimodal learning methods that integrate EHRs, biosignals, medical images, and other health data modalities. -
AI-enabled Knowledge Discovery for Health and Aging:
Harnessing AI to uncover actionable insights into health, disease progression, and aging across individuals and populations.
Selected Publications
∗equal contribution, †corresponding author
BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals
International Conference on Learning Representations (ICLR), 2026 (Oral)
npj Digital Medicine, 2026
DDIAgents: Predicting Drug Interactions by a Multi-Agent System with Dynamic Knowledge Flow
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2026 (AI4Sciences Track)
SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Models
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2025
ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions
ACM International Conference on Information and Knowledge Management (CIKM), 2025