معرفی
Dr. Primoz Skraba is a Professor in Applied and Computational Topology at the School of Mathematical Sciences, Queen Mary University of London. As Deputy Head of the Centre for Probability, Statistics and Data Science, he bridges theoretical topology with practical applications in data analysis, machine learning, and optimization.
- Education: PhD in Electrical Engineering from Stanford University (2009)
- Prior Roles: Positions at INRIA, France; Jozef Stefan Institute, Slovenia; University of Primorska; University of Nova Gorica
His research focuses on applying topological methods to analyze complex data. Key areas include:
- Stability of persistence diagrams for quantitative control in finite sampling
- Variants of persistence (zig-zag, robustness, multiparameter)
- Algorithmic Complexity in computational topology
- Stochastic Topology for random geometric models (Poisson, Boolean)
Recent publications emphasize persistent homology in random geometric complexes, universality theorems, and integrating topological methods into machine learning. He received grants from the Leverhulme Trust, EPSRC, and Alan Turing Institute for projects on topological universality and AI foundations. His advisee Gabryel Mason-Williams explores wireless sensor network applications of homology.
