Mohammed Osman
Kempner Graduate Fellow
PhD Student in Neuroscience
He/Him
About
Mohammed Osman is a computational neuroscientist interested in the structure, evolution, and neural basis of behavior. Using insights from dynamical systems theory and AI, he hopes to understand how the brain orchestrates successful interactions between animals and their environments. He has previously applied these approaches to topics like spatial navigation, motor sequencing, and sensory processing. Prior to starting his PhD in neuroscience, he completed a bachelor’s degree in symbolic systems and a master’s degree in computer science at Stanford University.
Research Focus
Osman’s current research focuses on computational neuroscience, machine learning, and animal behavior. He is principally interested in how coherent behavior on the level of an agent can emerge from messy, distributed interactions between its subsystems, as well as how the dynamics of neural activity enable neural networks to perform useful computations.