Theodor Misiakiewicz is a fifth year PhD student in the Statistics Department at Stanford University, advised by Andrea Montanari. He works on various topics in machine learning theory, statistics and applied probability. His current main interest is on providing a mathematical foundation for Deep Learning: in particular, he is working on their mean-field description and their connection in some regimes to Random Features model and kernel machines.
- Geometric Methods in Optimization and Sampling, Fall 2021. Visiting Graduate Student.