Explore a PhD research proposal that introduces a novel approach combining causality with neurosymbolic artificial intelligence to enhance automated reasoning in complex domains. Learn how this innovative framework transforms causal knowledge into neurosymbolic representations to improve expression and explainability while leveraging these representations to solve causal AI tasks. Discover the methodology for evaluating causal assumptions and constraints within neurosymbolic systems, and understand how this synergistic approach addresses the fundamental need for deep causal understanding in automated reasoning applications across rich, complex problem domains.