Projects per year
Personal profile
Chinese Name
殷可經
Biography
Dr. Kejing Yin is a Research Assistant Professor in the Department of Computer Science, Hong Kong Baptist University. Before his RAP appointment, he served as a Post-doctoral Research Fellow in the same department. He received his Ph.D. degree from the Department of Computer Science, Hong Kong Baptist University in 2021, and his Bachelor’s degree from the South China University of Technology in 2015. He was a visiting Ph.D. student at the College of Computing at Georgia Institute of Technology from Sep. 2019 to Feb. 2020. His research interests mainly focus on machine learning for high-dimensional healthcare data analytics, including computational phenotyping and predictive analytics for large-scale electronic health records (EHR) data. He serves as a program committee member or reviewer for international conferences, including AAAI, IJCAI, NeurIPS, ICLR, and ICHI.
Research Interests
- Machine Learning for Healthcare
- Healthcare Data Analysis
- Computational Phenotyping
- Temporal Data Analysis
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Dive into the research topics where Kejing YIN is active. Topic labels come from the works of this scholar.
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Collaborations and top research areas from the last five years
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Projects
- 2 Active
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AI Models Helping Combat Antibiotic Resistance in ICU – Personalized Decision Support for Empirical Antibiotic Therapy
YIN, K. (PI), CHEUNG, K. W. (CoI), ZHANG, L. (CoI), Tong, T. M. C. (CoI) & SIN, C. T. E. (CoI)
1/04/24 → 31/03/27
Project: Research project
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Addressing Asynchronicity in Clinical Multimodal Fusion via Individualized Chest X-ray Generation
Yao, W., Liu, C., Yin, K., Cheung, W. & Qin, J., 12 Dec 2024, 38th Conference on Neural Information Processing Systems, NeurIPS 2024. Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J. & Zhang, C. (eds.). Neural information processing systems foundation, p. 29001-29028 28 p. (Advances in Neural Information Processing Systems; vol. 37)(NeurIPS Proceedings).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
An End-to-end Learning Approach for Counterfactual Generation and Individual Treatment Effect Estimation
Wu, F., Yin, K. & Cheung, W. K., Jun 2024, Proceedings - 2024 IEEE Conference on Artificial Intelligence (CAI). Singapore: IEEE, p. 176-182 7 p.Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
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DNA-T: Deformable Neighborhood Attention Transformer for Irregular Medical Time Series
Huang, J., Yang, B., Yin, K. & Xu, J., Jul 2024, In: IEEE Journal of Biomedical and Health Informatics. 28, 7, p. 4224-4237 14 p.Research output: Contribution to journal › Journal article › peer-review
2 Citations (Scopus) -
DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency
Yao, W., Yin, K., Cheung, W. K., Liu, J. & Qin, J., 25 Mar 2024, Proceedings of the 38th AAAI Conference on Artificial Intelligence. AAAI press, p. 16416-16424 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 15).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access11 Citations (Scopus) -
Exploring high-quality microbial genomes by assembling short-reads with long-range connectivity
Zhang, Z., Xiao, J., Wang, H., Yang, C., Huang, Y., Yue, Z., Chen, Y., Han, L., Yin, K., Lyu, A., Fang, X. & Zhang, L., 31 May 2024, In: Nature Communications. 15, 1, 18 p., 4631.Research output: Contribution to journal › Journal article › peer-review
Open Access1 Citation (Scopus)