Tiffany Tang

Dr. Tiffany Tang is a Clare Boothe Luce Assistant Professor in the Department of Applied and Computational Mathematics and Statistics (ACMS) at the University of Notre Dame, within the College of Science. Her research focuses on developing interpretable statistical machine learning methods for healthcare applications, ensuring ethical AI use, and creating open-source tools like simChef for reproducible data science.

Education: Ph.D. in Statistics (UC Berkeley, 2023; advised by Bin Yu) and B.A./B.S. in Statistics/Mathematics (Rice University, 2018, Summa cum Laude).

Research Interests: Statistical machine learning for medicine, biomedical data analysis, and responsible AI deployment. Current projects include actionable insights from real-world data, transparent AI in healthcare, and open-source software for data science adoption.

Awards: Evelyn Fix Prize (2023), NSF GRFP (2019-2023), MIDAS Future Leaders Summit (2024), and Berkeley Outstanding Graduate Instructor Award (2019-2020). Over 20 publications in journals like Cell Reports Medicine and Journal of Machine Learning Research.

Teaching: Courses on data science tools and applications. Active contributor to pedagogical materials, including STAT 215A course development at UC Berkeley.

Service: Committee member for NISS Research Conference, judge for academic competitions, and organizer of workshops like the Berkeley-Stanford Veridical Data Science Workshop.