julesh

Jules Hedges is a prominent researcher at the intersection of mathematics and computer science, deeply involved in applying category theory to groundbreaking areas like economics, machine learning, and control theory. His research is driven by a vision towards what was historically termed cybernetics, offering a unique lens for understanding complex adaptive systems. He holds affiliations with the cutting-edge Institute for Categorical Cybernetics and the Mathematically Structured Programming group at the University of Strathclyde, where his work pushes theoretical boundaries.

Hedges' interests extend to graphical calculi, functional programming, proof theory, and the semantics of natural language, all contributing to his comprehensive approach to problem-solving. A prolific contributor, his recent publications include "Reinforcement learning in categorical cybernetics," accepted for ACT 2024, and "Bayesian open games," published by Compositionality. He also contributed to "The compositional structure of Bayesian inference" and "Value iteration is optic composition."

Beyond his extensive academic output, Jules is a vocal advocate for open access in research, being a signatory of the "No Free View? No Review!" pledge. This commitment underscores his dedication to accessible knowledge and collaborative scientific progress. His foundational work in compositional game theory provides a robust framework for analyzing complex interactions, making profound contributions to both theoretical computer science and practical applications. He actively shares his insights, including reading lists and lectures on compositional game theory for newcomers.