Daniel Yamins is a cognitive computational neuroscientist at Stanford University, where he's an assistant professor of Psychology and Computer Science, a faculty scholar at the Wu Tsai Neurosciences Institute, and an member of the Stanford Artificial Intelligence Laboratory. His research group focuses on reverse engineering the algorithms of the human brain, both to learn both about how our minds work and build more effective artificial intelligence systems. He is especially interested in how brain circuits for sensory information processing and decision making arise via the optimization of high-performing cortical algorithms for key behavioral tasks. He received his AB and PhD degrees from Harvard University, was a postdoctoral research at MIT, and has been a visiting researcher at Princeton University and Los Alamos National Laboratory. He is a recipient of an NSF Career Award, the James S. McDonnell Foundation award in Understanding Human Cognition, the Sloan Research Fellowship, and is a Simons Foundation Investigator.