Resume
Academic Achievements
- Research areas include statistical machine learning, scientific applications, open-source software & tools, interpretability, data integration/fusion, scientific reproducibility, cardiovascular genomics, precision cancer medicine, and work related to COVID-19. Developed simChef (R package), imodels (Python package), and causalDT (R package).
Research Experience
- Former postdoctoral researcher at the University of Michigan Statistics Department; currently an Assistant Professor in the Department of Applied and Computational Mathematics and Statistics (ACMS) at the University of Notre Dame.
Education
- PhD in Statistics from UC Berkeley, advised by Bin Yu; Postdoctoral researcher at the University of Michigan Statistics Department, working with Ji Zhu and Liza Levina.
Background
- Clare Boothe Luce Assistant Professor, with research interests primarily at the intersection of applied statistics/data science and medicine. Current research focuses on developing interpretable statistical machine learning methods to extract actionable and reliable insights from real-world data, ensuring transparent and responsible use of AI in healthcare, and creating open-source tools and software to facilitate community-wide use and adoption of reliable data science in practice.