Scholar
Ying Jin
Google Scholar ID: lT5KFUkAAAAJ
Assistant Professor, University of Pennsylvania
Citations & Impact
Citations
1,615
H-index
13
i10-index
15
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Papers: 'Pessimistic Policy Learning' selected by Annals of Statistics to present at the journal-to-conference track at NeurIPS 2025; paper on the predictive role of covariate shift in generalizability accepted to PNAS; organizing a NeurIPS 2025 workshop on Causality in Science (CauScien); giving a talk on optimal variance reduction in A/B testing at the ASA CPID webinar; organizing an invited session on generalizability, transportability, and distribution shift at ACIC 2025; gave a talk on the POPPER agent framework at the International Seminar on Selective Inference; proposed the POPPER framework for ensuring the soundness of what LLM agents acquire; proposed Optimized Conformal Selection for maintaining FDR control without sample splitting.
Research Experience
- Worked as a Wojcicki-Troper Postdoctoral Fellow at Harvard Data Science Initiative, collaborating with Professors José Zubizarreta and Marinka Zitnik; Currently helps organize the Online Causal Inference Seminar.
Education
- PhD in Statistics from Stanford University, graduated in 2024, advised by Professors Emmanuel Candès and Dominik Rothenhäusler; Bachelor's degree in Mathematics from Tsinghua University.
Background
- Research interests: Uncertainty quantification, generalizability, causality, and robustness. Professional field: Statistics and Data Science. Brief introduction: Assistant Professor in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania.
Miscellany
- Personal interests and other information not provided.
Co-authors