Taylor is a mathematical physicist and advisory researcher at Nettle, specializing in formal methods and reinforcement learning for intelligent system design. His research background includes neural network verification, the study of abstract domains, and mathematical modeling of decision-making processes.

By combining formal verification techniques with machine learning approaches, Taylor helps ensure that Nettle’s intelligent systems are both theoretically sound and practically effective. His work supports the development of solutions that are reliable, explainable, and adaptable to complex environments.