Qiuling Suo's Homepage

About Me

Short Bio

I am Qiuling Suo, a Ph.D. Student in Department of Computer Science and Engineering, The State University of New York at Buffalo, under the supervision of Dr. Aidong Zhang. Before joining UB, I got my Master's degree from Penn State University, and Bachelor's degree from Beihang University in China. My CV can be found here.

Research Interests

I am broadly interested in the areas of data mining, machine learning and health informatics, with an emphasize on improving model generalization on complex data. Due to the difficulty in data collection and data annotation process, real-world data (such as health data) are often incomplete, limited and heterogeneous. My work mainly focuses on mitigating the effect of two problems: data missingness and data scarcity. For data missingness, I consider two types of missingness: incomplete modalities in multi-modal learning (IJCAI19'_MeLIM), and missing values in time series analysis (BigData20'_GLIMA).

For the data scarcity issue, my work is based on the meta-learning paradigm. We develop a series of approaches with better generalization performance across domains/tasks for few-shot classification, including cross-domain learning with a single or multiple source domains (to appear), learning with non-stationary task distribution, and meta-learning in several application areas (KDD20'_TAdaNet, UbiComp21'_MetaTP).

Publications

Conference

MetaTP: Traffic Prediction with Unevenly-Distributed Road Sensing Data via Fast Adaptation [Paper]
Weida Zhong, Qiuling Suo, Abhishek Gupta, Xiaowei Jia, Chunming Qiao, and Lu Su
In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2021.

Heterogeneous Spatio-Temporal Graph Convolution Network for Traffic Forecasting with Missing Values [Paper]
Weida Zhong, Qiuling Suo, Xiaowei Jia, Aidong Zhang, and Lu Su
In 2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS), 2021.

Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness [Paper] [code]
Zhenyi Wang, Tiehang Duan, Fe Fang, Qiuling Suo, and Mingchen Gao
In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021.

GLIMA: Global and local time series imputation with multi-directional attention learning [Paper]
Qiuling Suo, Weida Zhong, Guangxu Xun, Jianhui Sun, Changyou Chen, and Aidong Zhang
In Proceedings of IEEE International Conference on Big Data (Big Data), 2020.

TAdaNet: Task-Adaptive Network for Graph-Enriched Meta-Learning [Paper] [Slides] [Video]
Qiuling Suo, Jingyuan Chou, Weida Zhong, and Aidong Zhang
In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020.

Metric Learning on Healthcare Data with Incomplete Modalities [Paper] [Code]
Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Jing Gao, and Aidong Zhang
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.

A Reliability-Aware Vehicular Crowdsensing System for Pothole Profiling [Paper]
Weida Zhong, Qiuling Suo, Fenglong Ma, Yunfei Hou, Abhishek Gupta, Chunming Qiao, and Lu Su
In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2019.

Multi-task Sparse Metric Learning for Monitoring Patient Similarity Progression [Paper]
Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Mengdi Huai, and Aidong Zhang
In 2018 IEEE International Conference on Data Mining (ICDM), 2018.

Metric Learning from Probabilistic Labels [Paper]
Mengdi Huai, Chenglin Miao, Yaliang Li, Qiuling Suo, Lu Su, and Aidong Zhang
In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018.

Risk Prediction on Electronic Health Records with Prior Medical Knowledge [Paper]
Fenglong Ma, Jing Gao, Qiuling Suo, Quanzeng You, Jing Zhou, and Aidong Zhang
In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018.

Uncorrelated Patient Similarity Learning [Paper]
Mengdi Huai, Chenglin Miao, Qiuling Suo, Yaliang Li, Jing Gao, and Aidong Zhang
In inProceedings of the 2018 SIAM International Conference on Data Mining (SDM), 2018.

A novel channel-aware attention framework for multi-channel EEG seizure detection via multi-view deep learning [Paper]
Ye Yuan, Guangxu Xun, Fenglong Ma, Qiuling Suo, Hongfei Xue, Kebin Jia, and Aidong Zhang
In 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2018.

A Multi-task Framework for Monitoring Health Conditions via Attention-based Recurrent Neural Networks [Paper] [Slides]
Qiuling Suo, Fenglong Ma, Giovanni Canino, Jing Gao, Aidong Zhang, Pierangelo Veltri, and Agostino Gnasso
In AMIA annual symposium proceedings, American Medical Informatics Association (AMIA), 2017

Personalized Disease Prediction Using A CNN-based Similarity Learning Method [Paper]
Qiuling Suo, Fenglong Ma, Ye Yuan, Mengdi Huai, Weida Zhong, Aidong Zhang, and Jing Gao
In 2017 IEEE International Conference onBioinformatics and Biomedicine (BIBM), 2017

Wave2Vec: Learning Deep Representations for Biosignals [Paper]
Ye Yuan, Guangxu Xun, Qiuling Suo, Kebin Jia, and Aidong Zhang
In 2017 IEEE International Conference on Data Mining (ICDM), 2017.

Risk Factor Analysis Based on Deep Learning Models [Paper]
Qiuling Suo, Hongfei Xue, Jing Gao, and Aidong Zhang
In Proceedings of ACM International Conference on Bioinformatics, Computational Biology, and HealthInformatics (BCB), 2016.

Journal

Learning Distance Metrics from Probabilistic Information [Paper]
Mengdi Huai, Chenglin Miao, Yaliang Li, Qiuling Suo, Lu Su, and Aidong Zhang
Transactions on Knowledge Discovery from Data (TKDD), 2019

Wave2Vec: Deep representation learningfor clinical temporal data [Paper]
Ye Yuan, Guangxu Xun, Qiuling Suo, Kebin Jia, and Aidong Zhang
NeuroComputing, 2019

Deep Patient Similarity Learning for Personalized Healthcare [Paper]
Qiuling Suo, Fenglong Ma, Ye Yuan, Mengdi Huai, Weida Zhong, Aidong Zhang, and Jing Gao
IEEE Transactions on Nanobioscience, 2018.

Workshop and Preprint

Learning to Aggregate: Generalizing Few-Shot Classification from Multiple Sources
Qiuling Suo, Baopu Li, Yuchen Bian, Zhenyi Wang, Guangtao Zheng, Weida Zhong, and Aidong Zhang
Manuscript

Automatic Channel Pruning via Graph Neural Network Based Hypernetwork
Qiuling Suo, Baopu Li, Yuchen Bian, and Aidong Zhang
Manuscript

Recurrent Imputation for Multivariate Time Series with Missing Values [Paper]
Qiuling Suo, Liuyi Yao, Guangxu Xun, Jianhui Sun, and Aidong Zhang
IEEE International Conference on Healthcare Informatics (ICHI), 2019

Feature Selection Model for Diagnosis, Electronic Medical Records and Geographical Data Correlation [Paper]
Giovanni Canino, Qiuling Suo, Pietro Hiram Guzzi, Giuseppe Tradigo, Aidong Zhang, and Pierangelo Veltri
In Proceedings of ACM International Conference on Bioinformatics, Computational Biology, and HealthInformatics (BCB), 2016.

Experiences

Internship

Research Intern, February 2020 - May 2020, IQVIA Inc.

Research Intern, September 2020 -, Baidu USA

Teaching Experiences

I was a teaching assistant for the following courses: CSE601: Data Mining and Bioinformatics. (2017Fall, 2019Fall)
CSE587: Data Intensive Computing. (2018Spring)
CSE574: Introduction to Machine Learning. (2018Fall)
CSE578: Distributed Systems. (2019Spring)

Qiuling Suo