معرفی
Eugene Katsevich is an Assistant Professor at the University of Pennsylvania's Wharton Department of Statistics and Data Science. His research spans statistical theory, methodology, and applications in genomics and computational biology.
- Education: Ph.D. in Statistics (Stanford, 2019), A.B. in Mathematics (Princeton, 2014)
His work focuses on:
- High-dimensional variable selection and multiple testing
- Conditional independence testing and computational efficiency
- Applications to genetics and genomics
- Development of statistical software for biological discovery
Recent publications address:
- Robust differential expression analysis in single-cell CRISPR screens
- Theoretical advances in false discovery rate control
- Multi-resolution causal variant localization
- CRISPRi-based enhancer-gene mapping
Scientific awards include:
- Wharton Undergraduate Teaching Excellence Award (2021)
He teaches courses in modern data mining (STAT4710/5710) and statistical methodology (STAT9610), and leads the Katsevich Lab at UPenn, funded by NSF and Analytics at Wharton. His research develops methods like KnockoffZoom and SCEPTRE for genome-wide analysis and single-cell CRISPR data.
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