| [TKDE] | Kejing Yin, Dong Qian, William K. Cheung. PATNet: Propensity-Adjusted Temporal Network for Joint Imputation and Prediction using Binary EHRs with Observation Bias. IEEE Transactions on Knowledge and Data Engineering, 2023. |
| [TIST] | Chin Wang Cheong, Kejing Yin, William K. Cheung, Benjamin C. M. Fung, Jonathan Poon. Adaptive Integration of Categorical and Multi-relational Ontologies with EHR Data for Medical Concept Embedding. ACM Transactions on Intelligent Systems and Technology, 2023. |
| [TKDE] | Kejing Yin, William K. Cheung, Benjamin C. M. Fung, Jonathan Poon. Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records. IEEE Transactions on Knowledge and Data Engineering, 2022. |
| [SDM-21] |
Kejing Yin, William K. Cheung, Benjamin C. M. Fung, Jonathan Poon.
TedPar: Temporally Dependent PARAFAC2 Factorization for Phenotype-based Disease Progression Modeling.
Proceedings of the 2021 SIAM International Conference on Data Mining,
2021.
acceptance ratio: 85⁄400 = 21.25% |
| [AAAI-21] |
Ardavan Afshar, Kejing Yin, Sherry Yan, Cheng Qian, Joyce C. Ho, Haesun Park, Jimeng Sun.
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence,
2021.
acceptance ratio: 1692⁄7911 = 21.4% |
| [KDD-20] |
Kejing Yin, Ardavan Afshar, Joyce C. Ho, William K. Cheung, Chao Zhang, Jimeng Sun.
LogPar: Logistic PARAFAC2 Factorization for Temporal Binary Data with Missing Values.
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
2020.
Research Track; acceptance ratio: 216⁄1279 = 16.9% |
| [JHIR] |
Kejing Yin, Liaoliao Feng, William K. Cheung.
Context-Aware Time Series Imputation for Multi-Analyte Clinical Data.
Journal of Healthcare Informatics Research,
2020.
This is an extension of our previous 2-page abstract appeared in ICHI-19. |
| [IJCAI-19] |
Lihong Song, Chin Wang Cheong, Kejing Yin, William K. Cheung, Benjamin C. M. Fung, Jonathan Poon.
Medical Concept Embedding with Multiple Ontological Representations.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence,
2019.
acceptance ratio: 850⁄4752 = 17.9% |
| [ICHI-19] | Kejing Yin, William K. Cheung. Context-Aware Imputation for Clinical Time Series. 2019 IEEE International Conference on Healthcare Informatics (Challenge track, 2-page abstract), 2019. |
| [AAAI-19] |
Kejing Yin, Dong Qian, William K. Cheung, Benjamin C. M. Fung, Jonathan Poon.
Learning Phenotypes and Dynamic Patient Representations via RNN Regularized Collective Non-negative Tensor Factorization.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence,
2019.
acceptance ratio: 1150⁄7095 = 16.2% |
| [IJCAI-18] |
Kejing Yin, William K. Cheung, Yang Liu, Benjamin C. M. Fung, Jonathan Poon.
Joint Learning of Phenotypes and Diagnosis-Medication Correspondence via Hidden Interaction Tensor Factorization.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence,
2018.
acceptance ratio: 710⁄3470 = 20% |
| [JAAS] |
Shunchun Yao, Lifeng Zhang, Kejing Yin, Kaijie Bai, Jialong Xu, Zhimin Lu, Jidong Lu.
Identifying laser-induced plasma emission spectra of particles in a gas–solid flow based on the standard deviation of intensity across an emission line.
Journal of Analytical Atomic Spectrometry,
2018.
This is an extension of my undergraduate final-semester project. |
| [E&F] |
Shunchun Yao, Yueliang Shen, Kejing Yin, Gang Pan, Jidong Lu.
Rapidly measuring unburned carbon in fly ash using molecular CN by laser-induced breakdown spectroscopy.
Energy & Fuels,
2015.
This is my undergraduate research. |