Weijieying Ren
Weijieying Ren

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Postdoctoral Fellow@Stanford University
  School of Medicine, the Department of Biomedical Data Science
  3174 Porter Drive, Palo Alto, CA 94304
  wjyren@stanford.edu | Google Scholar Google Scholar | DBLP

Short Bio

I am currently a postdoctoral fellow at Stanford University, affiliated with the School of Medicine, the Department of Biomedical Data Science, mentored by my amazing supervisor Prof. Nima Aghaeepour. Prior to this, I received my Ph.D. in May 2025 from the College of Information Sciences and Technology at Pennsylvania State University, where I was super lucky to be mentored by my best advisor Prof. Vasant Honavar.

I work on 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.

During my postdoc appointment, I shifted my focus to addressing real-world medical problems.
During PhD, my research centers on using ML/AI techniques to narrow the gaps between Data (Electronic Health Records (EHR) Data), Model (Continual Learning from Multi-modality Data), and Application (Clinical Conversational System):

News

Research

Full List | Google Scholar | DBLP

In Submission & Under-Review:

  1. Advancing Clinical Diagnosis Prediction with Foundation Models through Planning and Reasoning.
    Weijieying Ren, Xilong Ren, Tianxiang Zhao, WeiQin, Vasant G Honavar

  2. A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models.
    Weijieying Ren, Jingxi Zhu, Zehao liu, Tianxiang Zhao, Vasant G Honavar

  3. Survey of Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions.
    Weijieying Ren, Yuqing Huang, Tianxiang Zhao, Vasant G Honavar

Publications:

  1. Incorporating Biomedical Knowledge and Clinical Guidance into Electronic Health Record Based Machine Learning Systems for Healthcare
    Weijieying Ren, Dissertation

  2. DiaLLMs: EHR Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction
    Weijieying Ren, Tianxiang Zhao, Lei Wang, Tianchun Wang, Vasant G Honavar
    The 63rd Annual Meeting of the Association for Computational Linguistics (ACL-finding), 2025

  3. Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning
    Xinlong Li, Weijieying Ren, Wei Qin, Lei Wang, Tianxiang Zhao, Richang Hong
    2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

  4. RATT: A Thought Structure for Coherent and Correct LLM Reasoning
    Jinghan Zhang, Xiting Wang, Weijieying Ren, Lu Jiang, Dongjie Wang, Kunpeng Liu
    The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025

  5. TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules
    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

  6. Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data
    Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant G Honavar
    The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024

  7. EsaCL: An Efficient Continual Learning Algorithm
    Weijieying Ren, Vasant G Honavar
    In Proceedings of the SIAM International Conference on Data Mining (SDM), 2024

  8. Gradient-aware logit adjustment loss for long-tailed classifier
    Fan Zhang, Wei Qin, Weijieying Ren, Lei Wang, Zetong Chen, Richang Hong
    2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024

  9. T-SaS: Toward shift-aware dynamic adaptation for streaming data
    Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu
    In Proceedings of the 32nd ACM International on Conference on Information and Knowledge Management (CIKM), 2023

  10. Semi-supervised Drifted Stream Learning with Short Lookback
    Weijieying Ren, Pengyang Wang, Xiaolin Liu, Charles E.Hughes, etc.
    In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

  11. Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective
    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

  12. Cross-Topic Rumor Detection using Topic-Mixtures
    Weijieying 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

  13. Unsupervised Image Super-Resolution with an Indirect Supervised Path
    Zhen Han, Enyan Dai, Xu Jia, Weijieying Ren, Shuaijun Chen, Chunjing Xu, Jianzhuang Liu, Qi Tian
    The Conference on Computer Vision and Pattern Recognition Workshops (CVPR), 2019

  14. Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach
    Weijieying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, Enhong Chen
    In Proceedings of 22nd ICDM IEEE International Conference on Data Mining (ICDM), 2018

  15. Enhancing Semantic Representations of Bilingual Word Embeddings with Syntactic Dependencies
    Linli Xu, Wenjun Ouyang, Weijieying Ren, Yang Wang, Liang Jiang
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018

  16. Robust Mapping Learning for Multi-view Multi-label Classification with Missing Labels
    Weijieying Ren, Lei Zhang, Bo Jiang, Zhefeng Wang, Guangming Guo, Guiquan Liu
    Knowledge Science, Engineering and Management: 11th International Conference (KSEM), 2018

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 Adaptation of Machine Learning Models for Tabular Data (Submitted in 2023)
    Weijieying Ren, Xiaoting Li, Huiyuan Chen, Yuzhong Chen, etc.

Intern Experience

  1. Amazon, Applied Scientist Intern, May-Aug, 2024
  2. Visa Research, Applied Scientist Intern, May-Aug, 2023
  3. Amazon AWS, Applied Scientist Intern, May-Aug, 2022
  4. Noah’s Ark Labs, Jan-June, 2019

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