Today it was a pleasure to participate in the PhD defense of Yuqian Liu (NYU), who has exploited the world's largest dataset on stripped supernovae, part of the huge spectral collection of Maryam Modjaz's group at NYU. She pioneered various data-driven methods for the spectral analysis. One is to create a data-driven or empirical noise model using filtering in the Fourier domain. Another is to fit shifted and broadened lines using empirical spectra and bayesian inference. She uses these methods to automatically make uniform measurements of spectral features from very heterogeneous data from multiple sources of different levels of reliability. Her results rule out various (one might say: All!) physical models for these supernovae. Her results are all available open-source, and she has pushed her results into SNID, which is the leading software supernova classifier. Congratulations Dr Liu!