Rafael, originally from Cyprus, pursued his BSc in Mathematics at the University of Bristol, where he engaged in theoretical research on Interacting Particle Systems within Probability Theory. Seeking to explore more applied fields, he pursued an MSc in Statistics (Data Science) at Imperial College London. For his master’s project, Rafael employed Inverse Reinforcement Learning on Pedestrian Data to infer reward functions driving pedestrian movement. Then using the inferred reward functions trained Reinforcement Learning models to simulate pedestrian behavior in single-agent environments.
In his free time, Rafael enjoys traveling, playing guitar and singing, going to the gym, and loves animals, especially dogs.
At StatML, he aims to explore new areas of statistics, including his PhD focus on inverse problems in nuclear fusion. He also, plans to investigate how statistical methodologies are utilized across diverse fields such as finance, healthcare, environmental science, and technology.
