My research employs state-of-the-art machine learning methods to uncover the fundamental principles behind human cognition. I believe that to get a full understanding of the human mind, it is vital to consider it as a whole and not just as the sum of its parts. My long-term goal is to develop a unified theory of cognition, instantiated in models that can simulate, predict, and explain human behavior across a broad range of domains. Towards this end, I recently led the development of the first foundation model of human cognition.
Dr. Marcel Binz is a staff scientist and deputy head of the Institute for Human-Centered AI at Helmholtz Munich. His work is situated at the intersection of cognitive science and machine learning, aiming to uncover the computational principles of the human mind. He has published over thirty scientific articles, including papers in Nature, PNAS, Behavioral and Brain Sciences, and Psychological Review, as well as leading machine learning venues such as NeurIPS, ICML, and ICLR. His research has been featured in the New York Times, Der Spiegel, Frankfurter Allgemeine Zeitung, and been adapted into a children’s version for the Science Journal for Kids.