Xu Shi
Scholar

Xu Shi

Google Scholar ID: WGnAdnMAAAAJ
University of Michigan
Electronic Health RecordCausal InferenceNegative ControlMachine Translation
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Citations & Impact
All-time
Citations
3,624
 
H-index
24
 
i10-index
36
 
Publications
20
 
Co-authors
10
list available
Contact
No contact links provided.
Publications
18 items
Joint Modeling of Longitudinal EHR Data with Shared Random Effects for Informative Visiting and Observation Processes
2026
Cited
0
InternVLA-A1: Unifying Understanding, Generation and Action for Robotic Manipulation
arXiv.org · 2026
Cited
3
Leveraging Channel Knowledge Map for Multi-User Hierarchical Beam Training Under Position Uncertainty
2025
Cited
0
InternData-A1: Pioneering High-Fidelity Synthetic Data for Pre-training Generalist Policy
2025
Cited
0
A New Targeted-Federated Learning Framework for Estimating Heterogeneity of Treatment Effects: A Robust Framework with Applications in Aging Cohorts
2025
Cited
0
Time-to-Event Modeling with Pseudo-Observations in Federated Settings
2025
Cited
0
Adaptive Proximal Causal Inference with Some Invalid Proxies
2025
Cited
0
Distributed Kaplan-Meier Analysis via the Influence Function with Application to COVID-19 and COVID-19 Vaccine Adverse Events
2025
Cited
0
Resume (English only)
Academic Achievements
  • - Coding differences between Henry Ford Health System and Kaiser Permanente Northern California and differential utilization patterns
  • - The future does not affect the past: past health outcome is a negative control in air pollution study to mitigate unmeasured confounding
  • - Rare adverse event necessitates flexible propensity score methods
  • - Medical knowledge extraction from co-occurrence pattern in EHR and ICD code translation between Partners HealthCare and Veterans Health Administration: spherical data corrupted by mismatch
  • - Estimation of natural indirect effect robust to unmeasured confounding and measurement error in the mediator
Research Experience
  • - Associate Professor, Department of Biostatistics, University of Michigan
  • - Postdoctoral Fellow, Harvard Data Science Initiative, working with Tianxi Cai and Eric Tchetgen Tchetgen, Department of Biostatistics, Harvard TH Chan School of Public Health
  • - Co-leader of the Causal Inference Core of the FDA’s Sentinel Initiative Innovation Center, developing innovative statistical methods to monitor the safety of FDA-regulated medical products and exploring novel ways to utilize information from distributed EHR data partners
Education
  • - Ph.D. in Biostatistics, University of Washington, Advisors: Andrea Cook and Patrick Heagerty
  • - B.S. in Mathematics and Applied Mathematics (Minor in English), Chu Kochen Honors College of Zhejiang University, China
Background
  • Research interests include developing statistical methods for administrative healthcare data such as electronic health records (EHR) and claims data. Additionally, focuses on developing scalable and automated pipelines for curation and harmonization of EHR data across healthcare systems, and causal inference methods to harness the full potential of EHR data to address comparative effectiveness and safety questions.
Miscellany
  • Contact Information: shixu at umich.edu
  • Links: Google Scholar, University of Michigan
Co-authors
10 total
Bhramar Mukherjee
Bhramar Mukherjee
Professor of Biostatistics, Yale School of Public Health
Eric J Tchetgen Tchetgen
Eric J Tchetgen Tchetgen
University Professor
patrick heagerty
patrick heagerty
professor of biostatistics, university of washington
Co-author 4
Co-author 4
Co-author 5
Co-author 5
Co-author 6
Co-author 6
Andrew L. Beam
Andrew L. Beam
Chief Technology Officer, Lila Sciences | Associate Professor, Harvard University
Isaac Kohane
Isaac Kohane
Harvard Medical School, Children's Hospital, Brigham and Women's Hospital