Physics · Neuroscience · Computation · Decision-Making
Amida Anand
How do complex systems — from neurons to networks to societies — learn, adapt, and decide? And how can understanding them help us decide better?
Connecting theoretical physics, experimental neuroscience, and advanced computing to help people navigate complex, dynamic systems — and become better decision-makers.
- Researching learning in complex systems
- MRes Neurotechnology, Distinction
- Mentoring ISS experiments
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
Open questions
Questions I'm trying to answer
- How do complex systems learn, adapt, and reorganise themselves?
- What governs how brains allocate limited resources like memory and attention?
- How does structure at one scale shape behaviour at another?
- Can the mathematics of physics illuminate how intelligent systems decide?
- What, if anything, unites learning in brains and in machines?
Writing
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.