Professional Summary

Physician-scientist applying agentic AI to accelerate biomedical research. Currently using Claude Code to orchestrate multi-domain EHR phenotyping and genomics projects across respiratory viruses, sarcoidosis, HPV-associated cancers, long COVID prediction, and more. Track record developing validated computational methods at scale (400,000+ patient records, 500M+ observations) while maintaining clinical grounding that prevents AI outputs from diverging from biomedical reality.

Technical Skills

AI & Automation: Claude Code (agentic orchestration), Claude API, LLM-augmented research workflows

Programming & Analytics: Python, SQL, Polars, R, Google BigQuery, Google Cloud Platform, dsub, Google Batch

Statistical Methods: GWAS, PheWAS, phenotype risk scores, regression, propensity score matching, survival analysis

Healthcare Data: OMOP CDM, ICD, CPT, SNOMED, LOINC, RxNorm, EHR phenotyping, cohort development

Experience

Research Data Scientist

National Human Genome Research Institute, NIH | Aug 2023 – Present

  • Use Claude Code to orchestrate concurrent research projects across multiple disease domains (respiratory viruses, sarcoidosis, HPV-associated anal disease, long COVID, adverse drug events)
  • Architected distributed computing pipelines processing 155 survey-item PheWAS jobs and 26 ancestry-stratified GWAS using Google Batch/dsub
  • Developed phenotype risk score for long COVID prediction (AUC 0.94) that outperforms semi-supervised approaches, integrating wearable device data with EHR records
  • Built and validated computable phenotyping algorithms for 8 respiratory pathogens achieving 79-97% PPV; first-author publication in Scientific Reports (2025)
  • Lead multi-investigator projects spanning EHR-survey phenotype comparison for genetic discovery, clinical risk factor identification, and genetic variant validation

Infectious Diseases Clinical Fellow

National Institute of Allergy and Infectious Diseases, NIH | Jul 2021 – Jun 2026

  • Manage complex infectious disease cases providing clinical grounding that informs computational research design
  • Board certified in Internal Medicine, Pediatrics, and Adult Infectious Diseases

Medicine-Pediatrics Resident

University of Chicago Medicine | Jun 2017 – Jun 2021

  • Conducted retrospective EHR analysis identifying differential treatment responses in septic shock using machine learning-derived patient subgroups (American Thoracic Society Conference 2020)
  • Completed Summer Program in Outcomes Research Training (SPORT) fellowship

Graduate Student

NIH-Cambridge Scholars Programme, University of Cambridge | Aug 2010 – Nov 2016

  • Developed quantitative analysis pipelines for microscopy image data
  • First-author publication in Journal of Cell Science; co-authored Nature Cell Biology

Education

Degree Institution Year
Infectious Diseases Fellowship NIAID, NIH 2021–2026
Medicine-Pediatrics Residency University of Chicago 2017–2021
MD UT Southwestern Medical School 2008–2017
PhD, Clinical Biochemistry NIH, University of Cambridge 2010–2016
BA, Biology & Chemistry Texas Christian University 2004–2008

Selected Publications

Waxse BJ, Bustos Carrillo FA, Tran TC, Mo H, Ricotta EE, Denny JC. Computable phenotypes to identify respiratory viral infections in the All of Us research program. Scientific Reports. 2025;15(1):18680. DOI

Waxse BJ, Rao S. Data Science for Pediatric Infectious Disease: Utilizing COVID-19 as a Model. Current Opinion in Infectious Diseases. 2025;38(5):493-498. DOI

Goleva SB, Williams A, Schlueter DJ, Keaton JM, Tran TC, Waxse BJ, et al. Racial and Ethnic Disparities in Antihypertensive Medication Prescribing Patterns. Clin Pharmacol Ther. 2024;116(6):1544-1553.

Full publication list on NCBI

Selected Presentations

  • Waxse BJ, et al. Higher Step Count is Associated with Reduced Risk of Long COVID. IDWeek 2025, Accepted Podium.
  • Waxse BJ, Tran TC, Mo H, Denny JC. Identification and Validation of Common Respiratory Infections in All of Us. AMIA Annual Symposium, Podium. November 2024.

Contact

📧 bennettwaxse@gmail.com 📍 Washington, DC → Denver, CO (June 2026)

GitHub LinkedIn