Steven studies how long-term memory can improve decision making in reinforcement learning. He focuses on arranging collections of memories into graph structures, which he queries using graph neural networks. His research aims to improve the reasoning capabilities of robots, allowing them to solve human-level tasks and learn from and correct mistakes in real-time.