Antoine Cully is a Professor of Machine Learning and Robotics at Imperial College London (United Kingdom). His research focuses on designing novel machine learning approaches that enable robots to think outside the box, thereby enhancing their versatility and adaptability. In particular, he has developed Quality-Diversity optimisation algorithms, a new family of open-ended machine learning methods known for discovering creative solutions to challenging problems. His PhD dissertation from Sorbonne University has received three national Best-Thesis awards. He has published several journal papers in prestigious journals and conferences, including Nature, and top Robotics and AI venues. His work was featured on the cover of Nature (Cully et al., 2015), marking the first time Nature had featured an AI in Robotics paper on its cover. He also received the "Outstanding Paper of 2015" and "Outstanding Paper of 2020" awards from the Society for Artificial Life, the French "La Recherche" award (2016), and the Best Paper Award from GECCO in 2021, 2022, 2023, 2024, and 2025.