Michael Epitropakis is a Lecturer in Foundations of Data Science at Lancaster University. His research focuses on developing and analyzing novel stochastic search methodologies for solving complex real-life problems, that lie at the interface of Operational Research and Computer Science. These methods are interdisciplinary in character, adopting theory and practical methodologies from various scientific fields such is artificial intelligence, machine learning, and statistics. His work addresses both continuous (i.e. global) and discrete (i.e. combinatorial) problems. He is currently interested in applications of optimization to software engineering and to transportation. He has published more than 30 journal and conference papers. His research has been funded from both private and governmental funding agencies, including IEEE, Microsoft, European Union (ESF) and the Greek state research council.