Vlad Gonzalez

About

I am a Lecturer of Machine Learning and Data Science at Newcastle University, UK. My area of research is Responsible Artificial Intelligence (RAI), with a focus on algorithmic fairness and transparency. I have developed interpretable preprocessing methods to ensure distributive fairness in datasets, as well as a hybrid method to ensure fairness and data anonymisation. Currently I'm researching how to metricise and visualise procedural fairness. I am interested in interdisciplinary collaborations, particularly with people from the healthcare sector.

Selected publications

• Fair and Private Data Preprocessing through Microaggregation
• Optimising fairness through parametrised data sampling
• Towards Explaining the Effects of Data Preprocessing on Machine Learning
• Preprocessing matters: Automated pipeline selection for fair classification
• Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
• The relationship between trust in AI and trustworthy machine learning technologies