Feature Selection Model for Diagnosis, Electronic Medical Records and Geographical Data Correlation. - Giovanni Canino; Qiuling Suo; Pietro Hiram Guzzi; Giuseppe Tradigo; Aidong Zhang; Pierangelo Veltri (BCB, 2016)

Risk Factor Analysis Based on Deep Learning Models. - Qiuling Suo; Hongfei Xue; Jing Gao 004; Aidong Zhang (BCB, 2016)

A Multi-task Framework for Monitoring Health Conditions via Attention-based Recurrent Neural Networks. - Qiuling Suo; Fenglong Ma; Giovanni Canino; Jing Gao 004; Aidong Zhang; Pierangelo Veltri; Agostino Gnasso (AMIA, 2017)

Personalized disease prediction using a CNN-based similarity learning method. - Qiuling Suo; Fenglong Ma; Ye Yuan 006; Mengdi Huai; Weida Zhong; Aidong Zhang; Jing Gao 004 (BIBM, 2017)

Wave2Vec: Learning Deep Representations for Biosignals. - Ye Yuan 006; Guangxu Xun; Qiuling Suo; Kebin Jia; Aidong Zhang (ICDM, 2017)

A novel channel-aware attention framework for multi-channel EEG seizure detection via multi-view deep learning. - Ye Yuan 006; Guangxu Xun; Fenglong Ma; Qiuling Suo; Hongfei Xue; Kebin Jia; Aidong Zhang (BHI, 2018)

Multi-task Sparse Metric Learning for Monitoring Patient Similarity Progression. - Qiuling Suo; Weida Zhong; Fenglong Ma; Ye Yuan 006; Mengdi Huai; Aidong Zhang (ICDM, 2018)

Metric Learning from Probabilistic Labels. - Mengdi Huai; Chenglin Miao; Yaliang Li; Qiuling Suo; Lu Su 001; Aidong Zhang (KDD, 2018)

Risk Prediction on Electronic Health Records with Prior Medical Knowledge. - Fenglong Ma; Jing Gao 004; Qiuling Suo; Quanzeng You; Jing Zhou; Aidong Zhang (KDD, 2018)

Uncorrelated Patient Similarity Learning. - Mengdi Huai; Chenglin Miao; Qiuling Suo; Yaliang Li; Jing Gao 004; Aidong Zhang (SDM, 2018)

An Attention-based Recurrent Neural Networks Framework for Health Data Analysis. - Qiuling Suo; Fenglong Ma; Giovanni Canino; Jing Gao 004; Aidong Zhang; Agostino Gnasso; Giuseppe Tradigo; Pierangelo Veltri (SEBD, 2018)

Recurrent Imputation for Multivariate Time Series with Missing Values. - Qiuling Suo; Liuyi Yao; Guangxu Xun; Jianhui Sun; Aidong Zhang (ICHI, 2019)

Metric Learning on Healthcare Data with Incomplete Modalities. - Qiuling Suo; Weida Zhong; Fenglong Ma; Ye Yuan 006; Jing Gao 004; Aidong Zhang (IJCAI, 2019)

Wave2Vec: Deep representation learning for clinical temporal data. - Ye Yuan 006; Guangxu Xun; Qiuling Suo; Kebin Jia; Aidong Zhang (Neurocomputing, 2019)

A Reliability-Aware Vehicular Crowdsensing System for Pothole Profiling. - Weida Zhong; Qiuling Suo; Fenglong Ma; Yunfei Hou; Abhishek Gupta; Chunming Qiao; Lu Su 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019)

GLIMA: Global and Local Time Series Imputation with Multi-directional Attention Learning. - Qiuling Suo; Weida Zhong; Guangxu Xun; Jianhui Sun; Changyou Chen; Aidong Zhang (IEEE BigData, 2020)

TAdaNet: Task-Adaptive Network for Graph-Enriched Meta-Learning. - Qiuling Suo; Jingyuan Chou; Weida Zhong; Aidong Zhang (KDD, 2020)

Learning Distance Metrics from Probabilistic Information. - Mengdi Huai; Chenglin Miao; Yaliang Li; Qiuling Suo; Lu Su 001; Aidong Zhang (ACM Trans. Knowl. Discov. Data, 2020)

Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness. - Zhenyi Wang 001; Tiehang Duan; Le Fang; Qiuling Suo; Mingchen Gao (ICCV, 2021)

Heterogeneous Spatio-Temporal Graph Convolution Network for Traffic Forecasting with Missing Values. - Weida Zhong; Qiuling Suo; Xiaowei Jia; Aidong Zhang; Lu Su 001 (ICDCS, 2021)

MetaTP: Traffic Prediction with Unevenly-Distributed Road Sensing Data via Fast Adaptation. - Weida Zhong; Qiuling Suo; Abhishek Gupta; Xiaowei Jia; Chunming Qiao; Lu Su (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021)

Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions. - Zhenyi Wang 001; Li Shen 008; Le Fang; Qiuling Suo; Donglin Zhan; Tiehang Duan; Mingchen Gao (ECCV (20), 2022)

Improving Task-free Continual Learning by Distributionally Robust Memory Evolution. - Zhenyi Wang 001; Li Shen 008; Le Fang; Qiuling Suo; Tiehang Duan; Mingchen Gao (ICML, 2022)

Meta-learning without data via Wasserstein distributionally-robust model fusion. - Zhenyi Wang 001; Xiaoyang Wang; Li Shen 008; Qiuling Suo; Kaiqiang Song; Dong Yu 001; Yan Shen 002; Mingchen Gao (UAI, 2022)

MetaMix: Towards Corruption-Robust Continual Learning with Temporally Self-Adaptive Data Transformation. - Zhenyi Wang 001; Li Shen 008; Donglin Zhan; Qiuling Suo; Yanjun Zhu; Tiehang Duan; Mingchen Gao (CVPR, 2023)

Learning to Learn Task Transformations for Improved Few-Shot Classification. - Guangtao Zheng; Qiuling Suo; Mengdi Huai; Aidong Zhang (SDM, 2023)

Distributionally Robust Memory Evolution With Generalized Divergence for Continual Learning. - Zhenyi Wang 001; Li Shen 008; Tiehang Duan; Qiuling Suo; Le Fang; Wei Liu 005; Mingchen Gao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. - Mingfu Liang; Xi Liu; Rong Jin 001; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang 003; Jiyan Yang; et al. (WWW (Companion Volume), 2025)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. - Mingfu Liang; Xi Liu; Rong Jin 001; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang 003; Jiyan Yang; et al. (CoRR, 2025)