Research Interests: Machine Learning for Healthcare

My scientific goal is to advance the integration of machine learning into clinical practice by designing clinical AI systems that are informative, interactive, and affordable. My current research centers around narrowing the gaps between Data (Multi-source EHR data) , Model ( clinical foundation models), and Deployment (conversational system for lab test order and diagnosis consultant).

1. 🌻 Foundations of EHR Data Representation: Heterogeneity and Irregularity:
   • Representation Learing with Heteregeneous Data, e.g., tabualr data. (ICML 24, In-submission Survey)
   • Representation Learing with Irregular Longitidinal Data. (AAAI-24)
2. ⛵ Continual Learning with Multi-source Data and a Small Model:
   • Continual Learning from Multi-source Data (KDD-2022, ICDM-2022, CIKM-2023 )
   • Continual Learning with a Small Model and Intelligent Data. (SDM-2024)
3. 🌴 Towards Clinical Foundation models:
   • Towards Human-centered Clinical Foundation Model for Diagnosis Prediction (arxiv).
   • Clinical Foundation Models under Cost Pressure (In-submission)

Research

1. TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules. [PDF]
   Weijieying Ren, Xiaoting Li, Huiyuan Chen, Vineeth Mohan, Zhuoyi Wang, Mahaweta Das, Vasant G Honavar.
   The Forty-first International Conference on Machine Learning. (ICML-2024)
2. Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data.[PDF]
   Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant G Honavar.
   The 38th Annual AAAI Conference on Artificial Intelligence. (AAAI-2024)
3. EsaCL: An Efficient Continual Learning Algorithm.[PDF]
   Weijieying Ren, Vasant G Honavar.
   In Proceedings of the SIAM International Conference on Data Mining. (SDM-2024).
4. Gradient-aware logit adjustment loss for long-tailed classifier.[PDF]
   Fan Zhang, Wei Qin, Weijieying Ren, Lei Wang, Zetong Chen, Richang Hong.
   2024 IEEE International Conference on Acoustics, Speech and Signal Processing. (ICASSP-2024)
5. T-SaS: Toward shift-aware dynamic adaptation for streaming data.[PDF]
   Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu.
   In Proceedings of the 32nd ACM International on Conference on Information and Knowledge Management. (CIKM-2023)
6. Semi-supervised Drifted Stream Learning with Short Lookback.[PDF]
   Weijieying Ren, Pengyang Wang, Xiaolin Liu, Charles E.Huges, etc.
   In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (KDD-2022)
7. Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective.[PDF]
   Weijieying Ren*, Lei Wang*, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, etc. (* Equal Contribution)
   In Proceedings of 22nd ICDM IEEE International Conference on Data Mining. (ICDM-2022)
8. Cross-Topic Rumor Detection using Topic-Mixtures.[PDF]
   Xiaoying Ren, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu. The 16th Conference of the European Chapter of the Association for Computational Linguistics. (EACL-2021)
9. Unsupervised Image Super-Resolution with an Indirect Supervised Path[PDF]
   Zhen Han, Enyan Dai, Xu Jia, Xiaoying Ren, Shuaijun Chen, Chunjing Xu, Jianzhuang Liu, Qi Tian
   The Conference on Computer Vision and Pattern Recognition Workshops. (CVPR 2019 workshop)
10. Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach.[PDF]
    Xiaoying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, Enhong Chen.
    In Proceedings of 22nd ICDM IEEE International Conference on Data Mining. (ICDM-2018)
11. Enhancing Semantic Representations of Bilingual Word Embeddings with Syntactic Dependencies.[PDF]
    Linli Xu, Wenjun Ouyang , Xiaoying Ren , Yang Wang, Liang Jiang.
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence. (IJCAI-2018)
12. Robust Mapping Learning for Multi-view Multi-label Classification with Missing Labels.[PDF]
    Weijieying Ren, Lei Zhang, Bo Jiang, Zhefeng Wang, Guangming Guo, Guiquan Liu
    Knowledge Science, Engineering and Management: 11th International Conference. (KSEM-2018)

In Submission & Under-Review:

1. DiaLLMs: Advancing Clinical Diagnosis Prediction with Foundation Models through Planning and Reasoning.[PDF]
   Weijieying Ren, Tianxiang Zhao, Yuqing Huang, Vasant G Honavar
   
2. Survey of Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions.[PDF]
   Weijieying Ren, Tianxiang Zhao, Vasant G Honavar
   
3. Read, Diagnose and Chat: Towards Explainable and Interactive LLMs-Augmented Depression Detection in Social Media.[PDF]
   Wei Qin, Zetong Chen, Lei Wang, Yunshi Lan, Weijieying Ren, Richang Hong.
   

Patent:

1. Interpretable Neural Network for Tabular data Classification (Submitted in 2023)
   Weijieying Ren, Xiaoting Li, Huiyuan Chen, Yuzhong Chen, etc.
2. System, Method, and Computer Program Product for Analysis and/or Adaptation of Machine Learning Models for Tabular Data (Submitted in 2023)
   Weijieying Ren, Xiaoting Li, Huiyuan Chen, Yuzhong Chen, etc.