Chair of computational neuroscience. Co-author of the four-scale neuromodulatory framework SYMPHONY transposes from cortex to code. Lead of Objective O2 and co-lead of the ethics layer of O5.
Sri Ramaswamy is chair of computational neuroscience at Newcastle University’s School of Computing. His twenty-year arc moves from the digital reconstruction of cortical microcircuits at the Blue Brain Project at EPFL through an independent group on biologically-grounded artificial neural networks to the foundational framework that gives SYMPHONY its mathematical primary source: the four-scale neuromodulatory formulation in Trends in Neurosciences, 2022.
The pedigree is the moat. Mei, Muller & Ramaswamy (2022) is not a paper SYMPHONY references politely from a distance — it is the mathematical scaffolding on which O2 is built, with the third author as the consortium’s objective lead.
The 2022 paper formalised a four-scale framework for integrating neuromodulation into deep networks — hyperparameter scale (global gain), plasticity scale (connectivity reshape), neuronal scale (per-node gating), and dendritic scale (branch-local computation). The simulation evidence showed three behavioural properties that SYMPHONY requires from its substrate.
New tasks reach competence in fewer training steps than a non-modulated baseline.
Across task sequences the modulated network accumulates more reward than the static one.
The same network retains old skills as new ones land — the prerequisite for a substrate that survives an engineer's day.
SYMPHONY’s critical uncertainty is whether these three properties survive transposition from a continuous perceptual domain to a discrete symbolic one. That question is what O2 resolves.
Implement, on the substrate produced by O1, a computational instantiation of the four-scale framework of Mei, Muller & Ramaswamy (2022), adapted from continuous perceptual signals to discrete symbolic activations. Threshold: a single trained substrate demonstrates statistically significant (p < 0.01, paired test, ≥ 30 task instances) task-appropriate subnetwork activation across at least three distinct engineering task classes (localisation, impact analysis, refactoring candidate discovery), with F1 ≥ 0.6 versus expert-annotated relevance.
Newcastle co-leads the ethics layer of O5 — the equitable-access user study — bringing the school’s established protocol for stratified pre-registered behavioural studies in computing education.