About
A small lab with a long thesis.
Dissensus is an independent UK research lab investigating adversarial systems — where competing interests generate structural conflict — through computational, empirical, and theoretical work. Friction dynamics is the through-line.
What the lab is for
Dissensus is an independent UK research lab studying adversarial systems: the stability, alignment, and friction dynamics of systems in which competing interests generate structural conflict. The thesis is short. Wherever agents act together, action requires delegation, delegation produces friction, and friction has measurable stakes. We formalise the mechanics of friction, not to eliminate it (friction is the cost of existence in an adversarial environment) but to measure it, across markets, institutions, minds, and machines. The lab is independent by construction: no institutional affiliation, no external ownership, no funder with editorial reach. Everything the programme produces is open: papers, code, datasets, and tools, archived with DOIs so the work can be checked rather than taken on trust.
ASCRI — Adversarial Systems & Complexity Research Initiative
The research is organised under ASCRI, hosted at systems.ac: one programme, many fronts. A paper on cryptocurrency volatility and a paper on machine ethics look unrelated until you notice they are both probing how systems behave when their parts want different things.
Rules we hold ourselves to
These are written down in the charter — in public, where they can embarrass us if we break them.
Who does the work
Murad Farzulla
“We are more beholden to custom than reason; it is thus reason’s task to interrogate custom.”
I run Dissensus. My training is in finance — MSc Finance Analytics at King’s College London, after a First-Class BSc in Accounting & Finance at SOAS — and the research goes wherever the friction thesis leads: computational finance, political economy, AI alignment, formal methods. I develop the Axiom of Consent and Replicator-Optimization Mechanism frameworks the lab is organised around, and I hold the unfashionable view that a theory that cannot be computed, tested, or proved is not finished yet.
The full résumé lives at farzulla.org; the papers themselves are here, under Research.
Andrew Maksakov
Andrew keeps the lab’s empirical machinery running — distributed systems, GPU compute, and simulation pipelines — and is co-author on the ASRI systemic-risk index and the CBDC privacy-architecture work.
Felipe Pachano Azuaje, PhD
Felipe is an affiliated researcher contributing methodological perspectives across the programme — the standing outside view every small lab needs, without which a one-thesis lab starts agreeing with itself.
Four fronts, one thesis
Each domain is a different place to catch the same phenomenon in the wild. Publications in all four are listed under Research.
Applied work
The applied work exists because the research needed it first: the estimators are published, the proofs are machine-checked, and the reference index runs daily. Organisations engage Dissensus for friction analysis — mapping where competing interests generate structural conflict in a market, protocol, or organisation, and decomposing it into alignment, stake, and entropy — for bespoke ASRI-style systemic-risk indices, formal verification in Lean 4 with assumptions tracked in an explicit ledger, adversarial evaluation of multi-agent and agentic AI systems, and GARCH-family econometric and volatility modelling, including the open-source GJR-GARCH-X estimator we maintain.
Engagements take three shapes: advisory (a sceptical second opinion, with the mathematics attached), scoped research with a defined written deliverable, and custom tooling delivered with source, tests, and documentation. The lab is small and takes a few engagements at a time, so the research does not stall. Services is commercial and deliberately separate from partnership: a client owns the deliverable; funding the programme produces public goods. Write to research@dissensus.ai with the problem as you currently understand it. If we are not the right lab, we will say so.
Funding the programme
Funding accelerates a programme that already produces checkable artefacts: theorems verified in Lean 4, the ASRI systemic-risk index running daily at asri.dissensus.ai, and experiments that rerun from seed. The work exists; support makes more of it. The bottlenecks are concrete — compute for multi-agent and privacy experiments at proper scale, research-assistant time to carry results through to publication, and the unglamorous distance between working prototype and replicable finding. What partnership funds stays public: archived datasets, machine-checked Lean formalisations, and the live index — open by default.
There are three ways in. Grants and philanthropy fund the programme at project or programme level, with milestones agreed up front and outputs open by default. Academic partnership runs under ASCRI: joint proposals, co-authorship, shared infrastructure, visiting arrangements. Commercial problems belong on the Services side. One email to research@dissensus.ai is enough.
Independent by construction
The legal shape of the lab
Dissensus is the research brand of Dissensus Ltd, a company registered in England and Wales (no. 17309927). The independence is the point: the company answers to no institution, no outside owner, and no funder. The governance rules we hold ourselves to are written down in the charter — in public, where they can embarrass us if we break them.
Get in touch
We respond to substantive messages — and “substantive” is doing real work in that sentence. For funding, Partners above is the fuller picture; for commercial engagements, see Services; to collaborate on the research, start at Contribute.