Gabriel Tavares is a Ph.D. candidate in Computer Science at the University of Milan. He received his BSc and MSc at the Londrina State University (UEL) in 2019, while in 2014 he participated in an exchange program at the University of Michigan. Currently, his research activities focus on leveraging Process Mining analysis using Machine Learning methods. More specifically applying Meta-learning and Automated Machine Learning to unveil relationships between data characteristics and optimal pipelines. He has investigated themes such as automated Process Discovery, Trace Clustering, Event log encoding, Data Representation, Process Explainability, and Online Process Mining with particular attention to Concept Drift Detection.