Julio Martinez

Julio is an incoming PhD student at Stanford University interested in working on neural systems for planning, building models of theory-of-mind, and developing core models of intuitive physics. He hopes to build models that better explain how these processes are computed in the human brain while advancing the current state of AI. He will be advised by Dan Yamins and Noah Goodman. Currently, he's a Technical Associate in the Kanwisher lab at the McGovern Institute for Brain Research and the Center for Brains, Minds, and Machines (CBMM) at MIT where he works on understanding modular organization and task selectivity in artificial neural networks and the human brain. He also has experience working at Apple and Adobe applying machine learning to problems in predicting behavior and in classifying content in audio-visual data. He has an MS from the Institute for Computational & Mathematical Engineering (ICME) at Stanford University and a BS with a double major in Mathematics and Engineering Sciences/Structural Engineering from the University of California San Diego.