Ida Momennejad, PhD
Senior Reinforcement Learning
at Microsoft Research NYC
Zoom Meeting link:
Title: Multi-scale Predictive Representations
Memory and planning rely onlearning the relational structure of experience. A century after ?latentlearning’ experiments summarized by Tolman, the larger puzzle of cognitive mapsremains elusive: how does the brain learn compact representations of relationalstructures to guide flexible behavior? I use reinforcement learning (RL) tostudy how humans learn predictive representations in memory and planning. Ishow behavioral, fMRI, and electrophysiology evidence that hippocampal andprefrontal hierarchies learn multi-scale predictive representations updated viaoffline replay. This approach advances the century old notion of cognitive mapsand can inform biologicallyinspired artificial agents as well as computationalpsychiatry.
Ida Momennejad is a senior researcher in reinforcementlearning at Microsoft Research NYC. Ida builds and tests neurally plausiblealgorithms for learning the structure of the environment such that it servesmemory,exploration, & planning. Her approach combines reinforcementlearningwith behavioral experiments, fMRI, & electrophysiology. Ida gother BSc in software engineering (Tehran, Iran), MSc in Philosophy of Science(Utrecht, Netherlands), PhD in psychology/computational neuroscience (Berlin,Germany). She was a postdoc at Princeton and an associate research scientist atColumbia BME.