Jonathan Geuter

Hello! I’m a third year PhD student in Applied Mathematics in the ML Foundations group at Harvard University, advised by David Alvarez-Melis. I am fortunate to be supported by a Kempner Graduate Fellowship at the Kempner Institute for the Study of Natural & Artificial Intelligence. My current research focuses on developing new and efficient methods for LLMs, in particular for test-time scaling and model distillation. I also work on Optimal Transport (OT) for machine learning, and have utilized ideas from OT to derive rigorous machine learning algorithms. Further research interests of mine include Diffusion Models and Flow Matching, as these frameworks are underpinned by OT. Previously, I completed my Bachelor’s and Master’s in Mathematics at TU Berlin, including a year at UC Berkeley. Feel free to reach out, I’m always happy to discuss research ideas!