Ashwin is a Computational Cognitive Scientist exploring the foundations of intelligent behavior in humans and animals. His research focuses on reward-based learning, utilizing computational models of reinforcement learning to study human and animal learning behavior. He received his doctoral degree from Université Côte d’Azur, where he developed methods to reveal the evolving internal world representations of animals as they learn. At SCIoI, Ashwin is part of Project 59, which investigates how humans learn through observation. His work contributes to the synthetic aspect of the project, developing computational models to better understand observational learning in humans.