Tudor Manole takes on Assistant Professor of Statistics

Tudor will finish up as Norbert Wiener Postdoctoral Associate with MIT's Statistics and Data Science Center for a September 1st start in Sequoia Hall. He earned both MSc and PhD degrees in statistics at Carnegie Mellon University where, advised by Sivaraman Balakrishnan and Larry Wasserman, he received the Umesh K. Gavaskar Memorial PhD Thesis Award for 2024. Coming up next in November, Tudor is invited to present "How much can we learn from quantum random circuit sampling?" at the ASA Statistical Learning and Data Science Conference in New York and "Sharp deconvolution of optimal transport matchings" at the SIAM Conference on Mathematics of Data Science in Salt Lake City.

Tudor reports a broad interest in statistical theory, centered on optimal transport, latent variable models, machine learning, nonparametric hypothesis testing, and distribution-free inference. But much of his recent work has been motivated by interdisciplinary collaborations in the physical sciences, particularly in quantum computing and high-energy physics. Stanford is ready and waiting for Professor Manole!