['ACL'25: "SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence"', 'ICML'25: "Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting"', "NeurIPS'25: Insights from benchmarking Class-Imbalanced Tabular Learning", 'KDD'24: "AIM: Attributing, Interpreting, Mitigating Data-encoded Unfairness"', 'FAccT'24: "Group Fairness via Group Consensus" (with Eunice Chan)', 'ICML'24: "Class-Imbalanced Graph Learning without Class Rebalancing?"', "NeurIPS'24 Spotlight: Paper on Time Series Backdoor Attack", "ICLR'25: Co-authored paper on Test-Time Adaptation for Graph Structural Shift", 'KDD'23: "Web-based Long-term Spine Treatment Outcome Forecasting" (with Hangting Ye)', 'ICDE'23: "UADB: Unsupervised Anomaly Detection Booster" (with Hangting Ye)', 'NeurIPS'20: "MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler"', 'ICDE'20: "Self-paced Ensemble for Highly Imbalanced Massive Data Classification"', 'Recipient of the C.L. and Jane Liu Award (05/2025)', 'Open-source projects: IMBENS (imbalanced learning toolbox), Awesome2ML, Awesome-Imbalanced-Learning']