Lauro Langosco di Langosco

Lauro graduated with a Master’s in applied mathematics from ETH Zurich. He is primarily interested in the problems of AI corrigibility and alignment. Currently he is researching unusual ways in which deep learning systems can fail to generalize (for example by competently pursuing an objective different from the one they were trained on).

Prior to joining CHAI, Lauro worked on topics in probabilistic deep learning and the theory of stochastic optimization. He also co-organized Effective Altruism Zurich, helping run regular events, a conference on AI governance, and a reading group on AI alignment.