Kacper is a Research Fellow at the RMIT University, Australia. His main research focus is transparency – interpretability and explainability – of data-driven predictive systems based on artificial intelligence and machine learning algorithms. In particular, he has done work on enhancing transparency of predictive models with feasible and actionable counterfactual explanations and robust modular surrogate explainers. Kacper is the designer and lead developer of FAT Forensics – an open source fairness, accountability and transparency Python toolkit. He is also the lead author of a collection of online interactive training materials about machine learning explainability created in collaboration with the Alan Turing Institute – the UK's national institute for data science and artificial intelligence. Prior to joining RMIT he has held numerous research positions at the University of Bristol, UK, working with projects such as TAILOR – European Union's AI Research Excellence Centre.