Antonio Norelli

Antonio Norelli is a Researcher at the University of Oxford's Department of Computer Science, specializing in cutting-edge topics within Artificial Intelligence and Machine Learning. His work bridges theoretical advancements with practical applications, including AI in games, scientific discovery, and multimodal learning. He has contributed to projects like Olivaw, an Othello-playing AI, and explores foundational AI concepts such as explanatory learning and equivariant neural networks.

Research interests span from reinforcement learning in strategic games to latent space translation and representation learning. He investigates how AI can emulate human-like behavior and advance scientific methodologies through automated discovery and hypothesis generation. His contributions also address challenges in zero-shot learning and cross-modal adaptation without extensive training data.

Notable research includes analyzing the human-likeness of AI agents in games and quantifying the capabilities of language models. His publications reflect a focus on both technical innovation and ethical considerations in AI development.

No scientific awards, grants, or lab affiliations are publicly documented. He has not listed academic advisees, though his work suggests potential collaboration opportunities in AI and machine learning domains.