Hi, I'm Pranav.

I'm a NeuroAI researcher at the University of Oxford, studying minds as computational systems—agents that learn, adapt, and act purposefully in uncertain, open-ended environments. My work bridges AI and neuroscience, combining methods from AI (e.g. reinforcement learning, neural networks, and LLMs) with cognitive and computational neuroscience (e.g. controlled experiments, interpretability methods). I aim to both forward-engineer brain-inspired AI and reverse-engineer mechanisms of intelligence in humans, other animals and artificial neural networks.

I'm a theoretician at heart, my background is in engineering, and I like reinforcement learning, and all its variants! I did my PhD (submitted) on safe learning in humans and machines at the University of Oxford, and currently seeking postdoctoral opportunities. I've been fortunate to be advised by and to work with Prof. Peter Dayan, Prof. Ben Seymour, Prof. Ioannis Havoutis, Prof. Boris Gutkin, Prof. Flavia Mancini, and Prof. Sang Wan Lee.  Before my PhD, I had a brief stint at Nvidia, where I worked on scalable distributed deep learning.