Minds I think alongside

Established memory as a reconstructive, error-prone process — the foundation the whole argument rests on.

Separated recollection, familiarity, and confidence — evidence that subjective certainty is computed apart from memory content.

The neuroscience of decision and confidence — how a mind knows how much to trust its own conclusion.

A reader-centric account of neural syntax — meaning defined by what downstream circuits make of a signal.

The free energy principle — a single mathematics for how minds infer, learn, and act.

Showed memory as the physics of a system settling into a stable state. Nobel Prize in Physics, 2024.

Carried spin-glass physics into a theory of neural computation — the lineage my thesis sits in directly. Shared the 2024 Brain Prize.

Physics pushed to the edge of biology — what optimality and criticality really mean for living systems.

A physics of deep learning: why networks — brains and machines — learn the way they do.

The statistical mechanics of learning — the phase transitions hidden inside inference.

How humans and machines make decisions — and what each can teach us about the other.

Turned the physics of learning into the foundation of modern AI. Nobel Prize in Physics, 2024.

“Solve intelligence, and then use it to solve everything else.” Nobel Prize in Chemistry, 2024.

The molecular and synaptic basis of memory — how learning physically rewires neurons. Nobel Prize in Physiology or Medicine, 2000.

Place and grid cells — the brain’s cognitive map, which indexes memory and simulates possible futures. Nobel Prize in Physiology or Medicine, 2014.

How the remembering self and reconstructed memory bias judgment and choice. Nobel Prize in Economic Sciences, 2002.

Spin glasses and disordered systems — the physics my thesis borrows to model how networks learn. Nobel Prize in Physics, 2021.

Reinforcement learning — the theory of how an agent learns to decide from reward. A.M. Turing Award, 2024.

Deep learning — the architectures behind modern machine intelligence (with Geoffrey Hinton). A.M. Turing Award, 2018.

Foundations of computational and theoretical neuroscience — shared the 2024 Brain Prize with Haim Sompolinsky (above).

How the brain shares a scarce memory resource across competing demands. I worked in his lab.

The statistical physics of living matter. Supervised my MRes thesis on criticality.