| 2026 | KSEM | RLNA-Net: Reframing Document-Level Relation Extraction with Residual Attention. | Rongen Yan, Jinyi Zhan, Ye Tao, Feifei Qian, Shaolin Tan |
| 2025 | AAAI | DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification. | Feifei Qian, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu, Hangyuan Du, Edwin R. Hancock |
| 2025 | IJCAI | AKBR: Learning Adaptive Kernel-based Representations for Graph Classification. | Lu Bai, Feifei Qian, Lixin Cui, Ming Li, Hangyuan Du, Yue Wang, Edwin R. Hancock |
| 2025 | IJCAI | Exploring the Over-smoothing Problem of Graph Neural Networks for Graph Classification: An Entropy-based Viewpoint. | Feifei Qian, Lu Bai, Lixin Cui, Ming Li, Hangyuan Du, Yue Wang, Edwin R. Hancock |
| 2025 | ICRA | A Bio-Inspired Sand-Rolling Robot: Effect of Body Shape on Sand Rolling Performance. | Xingjue Liao, Wenhao Liu, Hao Wu, Feifei Qian |
| 2024 | CoRL | Learning Granular Media Avalanche Behavior for Indirectly Manipulating Obstacles on a Granular Slope. | Haodi Hu, Feifei Qian, Daniel Seita |
| 2024 | HRI | Modelling Experts' Sampling Strategy to Balance Multiple Objectives During Scientific Explorations. | Shipeng Liu, Cristina G. Wilson, Zachary I. Lee, Feifei Qian |
| 2020 | CogSci | Data Foraging: Spatiotemporal Data Collection Decisions in Disciplinary Field Science. | Cristina Wilson, Feifei Qian, Doug Jerolmack, Thomas F. Shipley, Sonia F. Roberts, Jonathan Ham, Daniel E. Koditschek |