Han Yu
Associate Professor
Works on trustworthy federated learning, ethical AI, crowdsourcing and trust management.
Han Yu's lab at NTU works on trustworthy & safe ML, data management & big data and interpretability, evaluation & safety of LMs. 195 papers since 2023, 78 at top venues, mostly NeurIPS and ICML. 13 PhD students. 15 alumni.
At a glance
- papers, 2023–2026
- 51/ year
- at T1 venues
- 40%
- PhD students
- 13
- MS students
- 0
- alumni listed
- 15
Papers by yearfrom the lab homepage, 2023–2026
- 45 papers2026 · T1 25 · collecting
- 46 papers2025 · T1 27
- 56 papers2024 · T1 15
- 48 papers2023 · T1 11
T1 venuesOtherVenues: NeurIPS, ICML, ICME, IJCAI, TKDE
Research focuspaper titles that use each topic's words
- Data management & big data20 papers
- Trustworthy & safe ML11 papers
- crowdsourcing3 papers
- ethical2 papers
- Interpretability, evaluation & safety of LMs1 paper
Paper list
From the lab homepage.
202645 papers
- KDD (T1)A Black Box Optimization-based Bidding Strategy for Data Consumers in Auction-based Federated Learning
- TPAMI (T1)Adaptive guidance for local training in heterogeneous federated learning. , IEEE (2026)
- ICML (T1)AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection
- Proceedings of the International Conference on Control, Robotics and CyberneticsAsymptotic Tracking Control with Guaranteed Performance under Unknown Control Coefficients and Time-Varying Parameters
- IEEE Transactions on Cognitive Communications and NetworkingCost-effective task offloading scheduling for hybrid mobile edge-quantum computing
- TKDE (T1)Counterfactual fairness prediction on missing data
- ICML (T1)Coupled Trigger Optimization and Vulnerable Parameter Alignment for Persistent Backdoor Attacks on Federated Learning
- ICML (T1)Cross-View Lewis Weight Fusion Empowering Exemplar Replay for Federated Class-Incremental Learning
- TNNLS (T1)Decoupling semantic and structural alignment for cross-domain federated learning
- Neural NetworksDFIR-DETR: Frequency-domain iterative refinement and dynamic feature aggregation for small object detection
- Transportation Research Part ADissociating ethical dilemma preferences and actions in autonomous driving by survey and driving experiment
- NeurIPS (T1)Distributionally Robust Black Box Optimization-based Bidding Strategy in Auction-based Federated Learning
202546 papers
- TNNLS (T1)A cost-aware utility-maximizing bidding strategy for auction-based federated learning
- NeurIPS (T1)A Reinforcement Learning-based Bidding Strategy for Data Consumers in Auction-based Federated Learning
- IEEE Communications Surveys and TutorialsAdvances and open challenges in federated foundation models
- Yu, H., Li, X., Xu, Z., Goebel, R. & King, I. (Eds.). Federated Learning in the Age of Foundation Models. Lecture Notes in Artificial IntelligenceBenchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning
- TKDE (T1)Camouflaged variational graph AutoEncoder against attribute inference attacks for cross-domain recommendation
- ICLR (T1)Can Textual Gradient Work in Federated Learning?
- NeurIPS (T1)Class-wise Balancing Data Replay for Federated Class-Incremental Learning
- ICML (T1)Commute Graph Neural Networks
- NeurIPS (T1)CrossSpectra: Exploiting Cross-Layer Smoothness for Parameter-Efficient Fine-Tuning
- ICMEDAG-AFL: Directed Acyclic Graph-based Asynchronous Federated Learning
- KDD (T1)Diffusion-Guided Diversity for Single Domain Generalization in Time Series Classification
- Big Data Mining and AnalyticsDomain-independent gear pitting fault diagnosis using transformer encoder and LinSoftmax
202456 papers
- IJCAI (T1)A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning
- IJCNNA Fair Incentive Mechanism for Federated Auctioning Networks
- IEEE Transactions on Intelligent Transportation SystemsAFM3D: An asynchronous federated meta-learning framework for driver distraction detection
- ICMEAgent-oriented Joint Decision Support for Data Owners in Auction-based Federated Learning
- Neural NetworksAggregating intrinsic information to enhance BCI performance through federated learning
- SIGIR (T1)An E-Commerce Dataset Revealing Variations during Sales
- IEEE Transactions on Big DataBiG-Fed: Bilevel optimization enhanced graph-aided federated learning
- IEEE Internet of Things JournalCooperative resource management in quantum key distribution networks for semantic communication
- IEEE Journal on Selected Areas in CommunicationsCost-efficient computation offloading in SAGIN: A deep reinforcement learning and perception-aided approach
- IJCAI (T1)Dual Calibration-based Personalised Federated Learning
- IEEE Transactions on Mobile ComputingEfficient and privacy-preserving feature importance-based vertical federated learning
- IEEE Transactions on Big DataEfficient asynchronous multi-participant vertical federated learning
202348 papers
- Knowledge-Based SystemsA multimodal approach for improving market price estimation in online advertising
- Knowledge-Based SystemsA novel KG-based recommendation model via relation-aware attentional GCN
- IEEE/CAA Journal of Automatica SinicaAchieving 500x acceleration for adversarial robustness verification of tree-based smart grid dynamic security assessment
- TKDE (T1)Adaptive memory networks with self-supervised learning for unsupervised anomaly detection
- Proceedings of the International Conference on Computing, Networking and CommunicationsAdaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning
- ACM Computing SurveysAI-empowered persuasive video generation: A survey
- TKDE (T1)AliExpress Learning-To-Rank: Maximizing online model performance without going online
- AI MagazineAutomatic product copywriting for e-commerce
- Knowledge-Based SystemsBayesian co-evolutionary optimization based entropy search for high-dimensional many-objective optimization
- Neural NetworksCapsule neural tensor networks with multi-aspect information for few-shot knowledge graph completion
- AI MagazineCAreFL: Enhancing smart healthcare with contribution-aware federated learning
- WWW (T1)Clustered Embedding Learning for Large-scale Recommender Systems
Where alumni went15 listed
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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