I design and analyze algorithms for optimization, Markov Chain Monte Carlo samplers, and generative models, with provable runtime, accuracy, and privacy guarantees for applications in Machine Learning, Artificial Intelligence, and Data Science.  In doing so, I aim to introduce new mathematical tools from physics and geometry to the design and analysis of optimization, sampling, and generative modeling algorithms used in ML and AI.