Hubert Wagner

Hubert Wagner is an Assistant Professor in Data Science at the University of Florida's Department of Mathematics, part of the College of Liberal Arts and Sciences. He teaches courses such as Computational Applied Topology and Linear Algebra for Data Science. Prior to joining UF, he completed a postdoctoral fellowship at IST Austria under Herbert Edelsbrunner and earned his PhD from Jagiellonian University under Marian Mrozek. His research focuses on developing topological algorithms and tools for practical applications in fields like astrophysics and biomedicine. Notably, he received the 2022 Google Research Scholar Award in Algorithms & Optimization for his work on Bregman divergences and topological methods in high-dimensional data analysis.

His research interests span computational geometry, topological data analysis, machine learning, and algorithm engineering. Recent projects include optimizing topological computations for large-scale imaging data (e.g., cosmic microwave background analysis) and detecting adversarial attacks on neural networks using persistent homology. He emphasizes practical applications through collaborations with industry and interdisciplinary research.

Hubert is actively involved in academic service, including course development and mentoring. His work has been published in leading venues such as SoCG and NeurIPS, with a focus on bridging theoretical foundations and real-world computational challenges.