Milan Bacchetta

Research interests

• Kernel Methods (Greedy Methods, Collocation for non-Linear PDEs)
• Optimization

Biography

Milan Bacchetta obtained his B.Sc. in Mathematics at the University of Tübingen, where he specialized in both convex optimization and functional analysis. His bachelor’s thesis focused on Proximal Gradient Descent for partially smooth functions. He then moved to the University of Stuttgart, where he explored various topics in functional analysis before eventually focusing on kernel methods and model order reduction. There, he wrote his thesis on Approximating Solutions to Non-Linear PDEs with Kernel Methods.

Since October 2025, he has been a PhD student at Saarland University, where he works on the TRAGO project. His current research is centered on this project, although he continues to maintain an active interest in kernel methods.