Dr. Primoz Skraba is a Senior Lecturer in Applied and Computational Topology. His research is broadly related to data analysis with an emphasis on topological data analysis. Generally, the problems he considers span both theory and applications. On the theory side, the areas of interest include stability and approximation of algebraic invariants, stochastic topology (the topology of random spaces), and algorithmic research. On the applications side, he focuses on combining topological ideas with machine learning, optimization, and other statistical tools. Other applications areas of interest include visualization and geometry processing. He has supervised 7 PhD students and 6 post-docs, is the Programme Director for the Master in Data Analytics, was a Fellow of the Alan Turing Insitute from 2018-2020, and has held grants from the European Commission (including being the Coordinator for an EU grant), ARRS, the Canadian Council of Natural Sciences, and the Alan Turing Institute.