Ziqi Xu

My proposal, “When Should Clinical AI Agents Act? Uncertainty-Aware Delegation for Reliable Decision-Making,” was selected for Anthropic’s AI for Science program, receiving $5,000 in credits to support research on trustworthy AI agents for clinical workflow. Read more in the WashU McKelvey Engineering press release.

I am happy to serve as a Graduate Student Advisory Board Member for the WashU Center for Career Engagement (2026–2027).

I wrapped up my summer internship at Apple in San Diego, where I worked on applied agentic workflows for hardware, and was invited to give my final presentation at Apple Park.

I presented “Using AI to Predict Post-Surgical Headache Improvement for Chiari I and Syringomyelia” at the Chiari Type I Annual Scientific Update alongside Dr. David Limbrick, Dr. Helia Hosseini, and Dr. Gabriel Haller.

My co-first-author work with Salim Yakdan, Real-Time Symptom and Wearable Monitoring May Improve Prediction of Postoperative Recovery in Lumbar Spine Surgery Beyond Standard Measures, has been published in Neurosurgery.

I was invited to present “Beyond Prediction: Trustworthy Multimodal AI for Pain” at the #Pain2026 Workshop: Artificial Intelligence and Pain, hosted by the Gulf Coast Consortia.

I was invited to present our work “Using AI to Predict Post-surgical Headache Improvement for Chiari I and Syringomyelia” at the 2026 THINK TANK Meeting in San Antonio, TX.

I will join Apple as a summer intern in San Diego, working on applied machine learning for display products. I’ll be focusing on leveraging large language models and transformer-based systems to support real-world products.

My work with Sizhe Wang (first author), CURA: Clinical Uncertainty Risk Alignment for Language Model–Based Risk Prediction, has been accepted to the Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL) 2026 main conference. This work was also featured in a press release.

My work with Dr. Jingwen Zhang (first author), Addressing Cohort Variability with Adaptive Fusion of Wearable and Clinical Data, has been accepted to ACM Transactions on Computing for Healthcare (HEALTH). This work was also featured in a press release.

I successfully defended my Ph.D. dissertation proposal on Trustworthy Multimodal AI for Personalized Healthcare!

As first author, I presented my work Incorporating Uncertainty in Predictive Models Using Mobile Sensing and Clinical Data at UbiComp 2025 in Helsinki, Finland.

My work with Claire Najjuuko (first author), Patterns of Maternal and Child Health Services Utilization and Associated Socioeconomic Disparities in Sub-Saharan Africa, has been accepted to Nature Communications. This work was also featured in a press release.

My work with Ben Warner (first author), Utilizing Semantic Textual Similarity for Clinical Survey Data Feature Selection, has been accepted to Findings of ACL 2025 (Vienna, Austria).

In collaboration with Braxton Goodnight, Dr. Dominic Sanford and Dr. Chenyang Lu, our team was selected as a winner of $50k in the Big Ideas Competition. Our project focuses on leveraging AI and multimodal health data to advance personalized and adaptive clinical decision-making.

As first author, Incorporating Uncertainty in Predictive Models Using Mobile Sensing and Clinical Data has been accepted to Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). This work was also featured in a press release.

My work with Claire Najjuuko (first author), Using Machine Learning to Predict Poor Adherence to Antiretroviral Therapy Among Adolescents Living with HIV in Low-Resource Settings, has been accepted to AIDS. This work was also featured in a press release.

As co-first author in collaboration with Dr. Sean Gupta, our paper Using Artificial Intelligence to Identify Three Presenting Phenotypes of Chiari Type-1 Malformation and Syringomyelia has been accepted to Neurosurgery. This work was also featured in a press release.

As first author, I presented my work Predicting Multi-dimensional Surgical Outcomes with Multi-modal Mobile Sensing at UbiComp 2024 in Melbourne, Australia.

As first author, Predicting Multi-dimensional Surgical Outcomes with Multi-modal Mobile Sensing has been accepted to Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). This work was also featured in WashU News and Health IT Analytics.

I successfully passed my Ph.D. Qualifying Exam!

As co-first author in collaboration with Dr. Jacob Greenberg and Dr. Madelyn R. Frumkin, our paper Preoperative Mobile Health Data Improve Predictions of Recovery from Lumbar Spine Surgery has been accepted to Neurosurgery.

My work with Dr. Xue Bing (first author), Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation, has been accepted to KDD 2023 (Long Beach, CA). This work was also featured in a press release.

I am excited to start my Ph.D. at Washington University in St. Louis, advised by Dr. Chenyang Lu.