Sherri Rose
Professor of Health Policy
Develops statistical machine learning and causal inference methods for fair health policy.
Sherri Rose's lab at Stanford works on learning theory & optimization, probabilistic & causal inference and efficient training & inference. 17 papers since 2023, 3 at top venues, mostly JAMIA and npj Digital Medicine. 4 PhD students. 38 alumni. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 18%
- PhD students
- 4
- MS students
- 0
- alumni listed
- 38
Papers by yearfrom the lab homepage, 2023–2026
- 3 papers2026 · T1 1 · collecting
- 4 papers2025 · T1 1
- 3 papers2024 · T1 0
- 7 papers2023 · T1 1
T1 venuesOtherVenues: JAMIA, npj Digital Medicine
Research focuspaper titles that use each topic's words
- health6 papers
- Learning theory & optimization3 papers
- Probabilistic & causal inference1 paper
- policy1 paper
- Efficient training & inference0 papers
Paper list
From the lab homepage.
20263 papers
- Medical Decision MakingA microsimulation-based approach for mitigating societal bias in chronic kidney disease data (opens in a new tab)
- Medical Decision MakingA novel decision modeling framework for health policy analyses when outcomes are influenced by social and disease processes (opens in a new tab)
- JAMIA (T1)Causal modeling of chronic kidney disease in a participatory framework for informing the inclusion of social drivers in health algorithms (opens in a new tab)
20254 papers
- JAMA Health ForumAI hype cycles and reality in health care (opens in a new tab)
- JAMA Health ForumAlgorithms to improve fairness in Medicare risk adjustment (opens in a new tab)
- Health Services ResearchIncidence, persistence, and steady-state prevalence in coding intensity for health plan payment (opens in a new tab)
- JAMIA (T1)Incorporating area-level social drivers of health in predictive algorithms using electronic health records (opens in a new tab)
20243 papers
- Proceedings of the Conference on Health, Inference, and LearningAlgorithmic changes are not enough: Evaluating the removal of race Adjustment from the eGFR equation (opens in a new tab)
- JAMA Health ForumDenial—Artificial intelligence tools and health insurance coverage decisions (opens in a new tab)
- BMJTRIPOD+AI statement: Updated guidance for reporting clinical prediction models that use regression or machine learning methods (opens in a new tab)
20237 papers
- JAMIA (T1)A call for better validation of opioid overdose risk algorithms (opens in a new tab)
- Annual Review of Statistics and Its ApplicationA review of generalizability and transportability (opens in a new tab)
- BiometricsConditional cross-design synthesis estimators for generalizability in Medicaid (opens in a new tab)
- Health AffairsMany clinicians implement digital equity strategies to treat opioid use disorder (opens in a new tab)
- BMJ OpenMeasuring concordance of data sources used for infectious disease research in the USA: A retrospective data analysis (opens in a new tab)
- npj Digital MedicineRecommendations for the use of pediatric data in artificial intelligence and machine learning: ACCEPT-AI (opens in a new tab)
- —Why machine learning cannot ignore maximum likelihood estimation (opens in a new tab)
Where alumni went38 listed
Apply to StanfordFall 2027
Stanford Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- See program page
Confirmed on the program page.
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- Papers
- The lab homepage
- Members
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Tiers are venue classifications, not lab rankings.
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