Max Kleiman-Weiner earned his PhD in Computational Cognitive Science from MIT in 2018 advised by Josh Tenenbaum and funded by the NSF and Hertz Foundation. His research focuses on formal models of human intelligence which inspire new algorithms and tools for building human-like AI. In particular, Max reverse-engineers human social intelligence by integrating Bayesian models of learning and multi-agent planning algorithms from artificial intelligence together with game theory and evolutionary dynamics. He won best paper at RLDM 2017 for models of human cooperation and the William James Award at SPP for computational work on moral learning. Previously, he was a Fulbright Fellow in Beijing (and speaks Mandarin), earned an MSc in Applied Statistics as a Marshall Scholar in Oxford, and did his undergraduate work at Stanford University as a Goldwater Scholar.
Max is now a Postdoctoral Fellow at Harvard's Data Science Initiative and the Center for Research on Computation and Society (CRCS). He is also co-founder and Chief Scientist of Diffeo, a start-up company based in Cambridge that creates algorithms that learn to collaborate with people by highting gaps in knowledge and uncovering new connections.