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Zhimei Ren is an Assistant Professor in the Department of Statistics and Data Science at the University of Pennsylvania, focusing on statistical methodology and its applications in data science. Ren obtained a Ph.D. in Statistics from Stanford University in 2021, studying under Emmanuel Candès. Following this, Ren worked as a Postdoctoral Researcher at the University of Chicago until 2023. Ren's research interests are diverse, encompassing distribution-free inference, multiple hypothesis testing, causal inference, survival analysis, and data-driven decision-making. Ren has contributed to prominent works such as 'Sensitivity analysis of individual treatment effects: a robust conformal inference approach' published in the Proceedings of the National Academy of Sciences and has multiple upcoming publications in journals like Annals of Statistics and Advances in Neural Information Processing Systems. Ren is actively involved in teaching various courses related to applied statistics and statistical theory, aiming to equip graduate students with both theoretical foundations and practical applications in statistics and data science.
University of Chicago • Chicago, IL
Conducted research in statistics and data science, leading to multiple publications in high-impact journals.
Wharton Doctoral programs cover fields like Finance, Marketing, Management, and Operations, Information and Decisions.