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Not insane just slightly eccentric
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Not insane just slightly eccentric

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studiofarzulla/README.md

Murad Farzulla

Independent researcher. Founder & Director of Dissensus Ltd, which runs the Adversarial Systems & Complexity Research Initiative — ASCRI.

I work on adversarial systems: coordination friction, systemic risk, multi-agent systems, and AI governance. Methods are computational finance and formal verification (Lean 4). Each paper takes the same friction dynamics into a different domain — crypto market microstructure, political governance, AI alignment.

ORCID Google Scholar arXiv SSRN

MSc Finance Analytics, King's College London · BSc Accounting & Finance (First Class), SOAS University of London


Live


Selected papers

Paper Status Link
Do Cryptocurrency Markets Differentiate Infrastructure from Regulatory Shocks? A Multi-Moment Event Study with Dependence-Robust Inference Under Review · Digital Finance arxiv:2602.07046
The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets Under Review · Computational Economics arXiv:2602.07018
Are Whitepaper Claims Reflected in Market Structure? A Contamination-Aware Pipeline and a Power-Limited Null Under Review · Financial Innovation arXiv:2601.20336
The Replicator-Optimization Mechanism: A Scale-Relative Formalism for Persistence-Conditioned Dynamics Preprint arXiv:2601.06363
The Axiom of Consent: Friction Dynamics in Multi-Agent Coordination Preprint arXiv:2601.06692
Context-Dependent Affordance Computation in Vision-Language Models Preprint arXiv:2603.04419

Full list with PDFs → dissensus.ai · farzulla.org (papers + CV)


dissensus.ai · systems.ac · Google Scholar · ORCID 0009-0002-7164-8704 · murad@dissensus.ai

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  1. asri asri Public

    ASRI: Aggregated Systemic Risk Index for Cryptocurrency Markets — paper + real-time monitoring system | DAI-2509 | Dissensus AI Working Paper

    Python 2

  2. extremity-premium extremity-premium Public

    The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets — ABM + paper | DAI-2510 | Dissensus AI Working Paper

    Python

  3. autonomous-red-team autonomous-red-team Public

    Autonomous Red Team: Multi-Agent Adversarial Security Testing — paper + proof-of-concept framework | DAI-2513 | Dissensus AI Working Paper

    Python 6

  4. lean-formalizations lean-formalizations Public

    Machine-checked proofs in Lean 4 + Mathlib for results across four research papers on quantum foundations, friction dynamics, evolutionary game theory, and structural identity.

    Lean

  5. gjr-garch-x gjr-garch-x Public

    GJR-GARCH models with exogenous variance regressors

    Python 2

  6. friction-marl friction-marl Public

    Multi-Agent Reinforcement Learning with Friction Dynamics — code companion to Axiom of Consent (DAI-2601)

    Python