معرفی
Simon Weber is a researcher affiliated with the ETH Zurich (Department of Computer Science). His work focuses on Unique Sink Orientations (USOs), a combinatorial abstraction of optimization problems like Linear and Quadratic Programming.
Simon's research spans three areas: (1) Structure of USOs and their links to Oriented Matroids; (2) Constructions of high-dimensional USOs to analyze algorithm complexity; and (3) Algorithmic improvements for sink-finding. He also explores topics in graph compression, neural networks, and ∃R-complete problems.
- Key Publications: PhD thesis on USO reductions, ∃R-completeness in neural training, and USO phase analysis.
- Scientific Contributions: Advances in USO complexity, FPT algorithms for MaxCut, and recognition of geometric hypergraphs and nerves of convex sets.
He has supervised multiple theses at ETH Zurich, including topics on USO visualization, MaxCut algorithms, and necklace splitting. His teaching experience includes being a Head Assistant for courses like Geometry: Combinatorics & Algorithms and Topological Data Analysis. Simon's work has been recognized with Best Paper and Best Student Paper Finalist awards at SC19.
