CV
Ziqi Xu
Summary
AI for health care, with a focus on multimodal trustworthy AI for clinical decision support and personalized interventions. My research integrates wearable and mobile sensing data, clinical text, and electronic health records (EHR) to develop uncertainty-aware predictive models of clinical outcomes that enable reliable, transparent, and human-centered decision-making in surgery and perioperative care.
Education
- Ph.D. in Computer ScienceMay 2027 (Expected)Washington University in St. LouisGPA: 4.0/4.0
- B.S. in Computer Science and Mathematics (double major)May 2022Washington University in St. LouisGPA: 3.99/4.0Courses: Machine Learning, Data Mining, Language Models
Work Experience
- Research Assistant2022-07-01 -Washington University in St. Louis (AI for Health Institute)Advisor: Prof. Chenyang Lu
- Developed an uncertainty-aware multimodal ML framework to predict persistent post-surgical pain by integrating mobile sensing, ecological momentary assessment (EMA), and structured clinical data; proposed view-specific uncertainty estimation and a global confidence score to improve predictive performance and interpretability for clinical deployment.
- Designed a multitask, multimodal learning framework to predict surgical outcomes (pain interference, physical function, recovery quality) using wearable and EMA time-series data; introduced dynamic task weighting to mitigate negative transfer and improve over single-task and clinical baseline models.
- Built an LLM-based framework for clinical outcome prediction from unstructured notes with uncertainty quantification; incorporated variational inference and ensemble methods to identify low-confidence predictions and support human-in-the-loop decision making; evaluated on MIMIC-IV and real-world clinical notes.
- Developed an unsupervised learning pipeline to identify clinically meaningful phenotypes of Chiari Type I malformation with syringomyelia by combining Laplacian feature selection with expert-curated variables to enable interpretable clustering.
- Contributed to ML models for predicting poor adherence to antiretroviral therapy among adolescents with HIV using a six-year longitudinal dataset; applied unsupervised clustering to identify high-risk populations and inform targeted interventions.
- Software Engineer2021-05-01 - 2021-07-01ORKA Health Technology Co., LtdShanghai, China
- Developed a mobile application for smart hearing aids serving 50+ users with clinically verified hearing impairments; implemented core features in Flutter including authentication, mode control, and modular UI.
- Performed A/B testing and user behavior analysis using SQL-based event tracking, informing design improvements and enhancing accessibility and user engagement.
Publications
- Incorporating Uncertainty in Predictive Models Using Mobile Sensing and Clinical Data: A Case Study on Persistent Post-Surgical Pain2025Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (UbiComp)Z. Xu, J. Zhang, S. Haroutounian, H. Liu, Z. Cao, G. R. Messner, H. B. Alaverdyan, S. Ahuja, R. Koshy, J. Hanns, M. Frumkin, T. L. Rodebaugh, C. Lu.
- Predicting Multi-Dimensional Surgical Outcomes with Multi-Modal Mobile Sensing2024Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (UbiComp)Z. Xu, J. Zhang, J. Greenberg, M. Frumkin, S. Javeed, J. Zhang, B. Benedict, K. Botterbush, T. L. Rodebaugh, W. Ray, C. Lu.
- CURA: Clinical Uncertainty Risk Alignment for Language Model–Based Risk Prediction2026Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)S. Wang, Z. Xu, C. Najjuuko, Y. Wu, C. Alba, C. Lu. Accepted.
- Utilizing Semantic Textual Similarity for Clinical Survey Data Feature Selection2025Findings of the Association for Computational Linguistics (ACL)B. C. Warner, Z. Xu, S. Haroutounian, T. Kannampallil, C. Lu.
- Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation2023ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD)B. Xue, A. Said, Z. Xu, H. Liu, N. Shah, H. Yang, P. Payne, C. Lu.
- Using Artificial Intelligence to Identify Three Presenting Phenotypes of Chiari Type-I Malformation and Syringomyelia2024NeurosurgeryV. P. Gupta*, Z. Xu* (*equal contribution), J. K. Greenberg, J. M. Strahle, G. Haller, T. Meehan, A. Roberts, D. D. Limbrick Jr., C. Lu.
- Preoperative Mobile Health Data Improve Predictions of Recovery from Lumbar Spine Surgery2024NeurosurgeryJ. K. Greenberg*, M. Frumkin*, Z. Xu* (*equal contribution), J. Zhang, S. Javeed, J. Zhang, B. Benedict, K. Botterbush, S. Yakdan, C. A. Molina, B. H. Pennicooke, D. Hafez, J. I. Ogunlade, N. Pallotta, M. C. Gupta, J. M. Buchowski, B. Neuman, M. Steinmetz, Z. Ghogawala, M. P. Kelly, B. R. Goodin, J. F. Piccirillo, T. L. Rodebaugh, C. Lu, W. Z. Ray.
- Patterns of Maternal and Child Health Services Utilization and Associated Socioeconomic Disparities in Sub-Saharan Africa2025
- Addressing Cohort Variability with Adaptive Fusion of Wearable and Clinical Data: A Case Study in Predicting Pancreatic Surgery Outcomes2026ACM Transactions on Computing for HealthcareJ. Zhang, R. Wang, Z. Xu, H. Liu, J. Rodriguez, H. Cos, R. Srivastava, L. Raper, D. Sanford, C. Hammill, C. Lu.
Presentations
- Leveraging Preoperative Mobile Health Data to Predict 1-Year Recovery Outcomes After Lumbar Spine Surgery2026Neurosurgery (Abstract, Supplement 1)S. Yakdan*, Z. Xu* (*equal contribution), et al. doi: 10.1227/neu.0000000000003964_202
- Minimum Clinically Important Differences in Quantitative Objective Markers of Physical Function in Patients Undergoing Lumbar Spine Surgery2025Neurosurgery (Abstract, Supplement 1)J. Zhang, S. Yakdan, et al. doi: 10.1227/neu.0000000000003360_414
- Machine learning and lumbar spondylolisthesis2023Seminars in Spine SurgeryS. Yakdan, K. Botterbush, Z. Xu, C. Lu, W. Z. Ray, J. K. Greenberg. doi: 10.1016/j.semss.2023.101048
Teaching
- Guest Lecturer, PHS 5100-01: Development, Validation and Application of Risk Prediction Models2026Washington University in St. LouisRole: Guest Lecturer
- CSE 419A: Introduction to AI for Health2024Washington University in St. LouisRole: Assistant Instructor
- CSE 531A: AI for Health2024Washington University in St. LouisRole: Assistant Instructor
- CSE 417: Introduction to Machine Learning2023Washington University in St. LouisRole: Teaching Assistant
- CSE 240: Logic and Discrete Mathematics2020Washington University in St. LouisRole: Teaching Assistant