Lukas Fesser
Kempner Graduate Fellow
Ph.D. Student in Applied Mathematics
Contact Information
Areas I Research:
About
Lukas Fesser is a Ph.D. student in the Applied Mathematics program at Harvard University, where he concurrently pursues an M.Sc. in Computer Science. His research is advised by Melanie Weber and focuses on machine learning in non-Euclidean domains. Prior to joining Harvard, Fesser studied Mathematics and Computer Science at the University of Oxford. While there, he developed curvature-based community detection methods in complex networks with Renaud Lambiotte and investigated provable robustness properties of vision transformer models with Marta Kwiatkowska. In his free time, he enjoys reading, rowing, and playing tennis.
Research Focus
Fesser’s current research focuses on graph machine learning: he is broadly interested in understanding how these models can be made more powerful and reliable, both theoretically and empirically. He is also especially passionate about applications in healthcare and AI-supported scientific discovery.