Today we’re joined by Sherri Rose, Associate Professor at Harvard Medical School.
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Sherri’s research centers around developing and integrating statistical machine learning approaches to improve human health. We cover a lot of ground in our conversation, including the intersection of her research with the current COVID-19 pandemic, the importance of quality in datasets and rigor when publishing papers, and the pitfalls of using causal inference. We also touch on Sherri’s work in algorithmic fairness, including the necessary emphasis being put on studying issues of fairness, the shift she’s seen in fairness conferences covering these issues, and her paper “Fair Regression for Health Care Spending.”
Connect with Sherri!
- Paper: Intersections of machine learning and epidemiological methods for health services research
- The Summer Institute for Biostatistics
- Responsible Data Science in the Fight Against COVID-19
- Paper: Fair Regression for Health Care Spending
- AI for Social Good: Why “Good” isn’t Enough with Ben Green
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“More On That Later” by Lee Rosevere licensed under CC By 4.0