Tyler Cody is an associate professor of data science at the University of Virginia, where he leads the AGI Lab within the School of Data Science. His foundational research concerns the philosophy and mathematics of learning, intelligence, and consciousness from a systems-theoretic lens. He also develops systems engineering and design frameworks and methods for applications of artificial intelligence.
Cody posits that abstract systems theory offers an advantageous means of considering learning without explicit reference to solution methods and, moreover, a way to stratify the assumptions underlying learning phenomena into appreciable levels of abstraction. The general systems nature of learning cannot be escaped; solution methods necessarily inherit it.
His current topical work includes space systems, scaling laws, and “AI tokens” (2025+). Previously, his applied research centered on cyber-physical systems with learning components (2018–2025). Rather than treating these as unrelated topics and application areas, he uses them to investigate recurring questions about change and reuse, lifecycles, and iterated games.
