Physics · Neuroscience · Computation · Decision-Making
Amida Anand
Understanding how minds learn and decide.
So people, and the systems they build, can choose better — and build a better world.
- Researching learning in complex systems
- MRes Neurotechnology, Distinction
- Mentoring ISS experiments
Mission
Toward a humanity that decides better.
Every future we build is decided by minds. I work to understand how intelligence learns and decides — and to turn that understanding toward a wiser world.
Read the missionCuriosity
Questions I'm trying to answer
The open problems driving the work — from how memory reconstructs the past to how any mind learns to decide.
Explore my thinking →Research
Decoding the learning brain
Work that bridges physics, neuroscience, and computation — on how complex, adaptive systems learn, allocate resources, and reorganise.
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Two Criticalities
Applying renormalisation group methods and spin glass theory to model the critical behaviour underlying how biological neural networks learn and consolidate memory.
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Visual Working Memory
How the brain distributes a limited working-memory resource across competing visual items — research internship under Dr Paul Bays.
Publications
Peer-reviewed, 2025
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Computational analysis of learning in young and ageing brains
Frontiers in Computational Neuroscience, 19:1565660
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Brain Inspired Learning for Neural Networks
EANN 2025 · Communications in Computer and Information Science, vol. 2581, pp. 59–72, Springer, Cham
Thinking
Notes & essays
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Memory is not retrieval — it is inference
A short case for treating memory as a dynamical, subjective reconstruction rather than a stored recording read back on demand.
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Why a physicist should care about how brains learn
Criticality, spin glasses, and renormalisation are not metaphors borrowed to sound rigorous — they are the natural language for a learning system.