ORGANIZATIONAL CHARTER

Status: Self-funded research activity operated by an individual
Trading Name: Farzulla Research
Established: October 2025
Location: London, United Kingdom
Researcher: Murad Farzulla

This is not a registered charity or company; it is a one-person research project publishing open datasets, software, and preprints.

Farzulla Research conducts independent research at the intersection of quantitative finance, cybersecurity, and artificial intelligence. We build working systems that demonstrate novel approaches to autonomous security, financial modeling, and machine learning, emphasizing reproducibility, open source tooling, and practical implementation.

Adversarial AI Systems

Multi-agent security frameworks, autonomous red team/blue team competitions

Quantitative Finance

Market microstructure analysis, regulatory event studies, volatility modeling

Applied Machine Learning

Local LLM deployment, RAG systems, semantic supervision methodologies

Financial Crime Detection

OSINT-based fraud analysis, regulatory compliance mechanisms

Research Infrastructure

Kubernetes-native compute clusters, distributed systems for AI research

Build First: Working prototypes demonstrate feasibility before formal publication

Open Source: Code, methodologies, and datasets released publicly where possible

Independence: Research direction determined by interesting problems, not funding requirements

Reproducibility: Documentation-first approach ensures replicability

All research outputs comply with OpenAIRE Guidelines for open access and FAIR data principles:

• All research outputs publicly accessible via Zenodo repository with DOI assignment
• CC-BY 4.0 licensing (default) for publications
• Open source software releases (MIT/Apache licenses)
• Standardized metadata following OpenAIRE requirements
• ORCID integration for author identification (0009-0002-7164-8704)
• Research data management aligned with European infrastructure standards

Zenodo Community: zenodo.org/communities/farzulla

Academic Papers

Substrate-independent friendship theory, computational trauma frameworks, statistical alpha asymmetries in FX markets, MSc thesis on cryptocurrency volatility (2025), undergraduate AML policy analysis (2024)

Open Source Projects

• Adversarial Security Agents (DOI: 10.5281/zenodo.XXXXX) - Kubernetes-native offensive security framework
• Tensor-DeFi Framework (DOI: 10.5281/zenodo.XXXXX) - Market microstructure analysis via tensor decomposition
• Creative AI Trainer - Semantic supervision for model fine-tuning
• Cryptocurrency Event Study - GARCH/TARCH econometric analysis

All outputs archived with permanent identifiers via Zenodo

Technical Documentation

Session logs, deployment guides, architectural decisions

Public Datasets

Curated security knowledge bases, financial event classifications

Murad Farzulla, MSc Finance Analytics (in progress)

Education:
• MSc Finance Analytics, King's College London (2024 to 2026)
• BSc Accounting and Finance (First Class Honours), SOAS University of London (2021 to 2024)

Research Interests:
Adversarial systems, autonomous AI agents, financial crime detection, market microstructure, computational infrastructure

Email: murad@farzulla.org
ORCID: 0009-0002-7164-8704
GitHub: github.com/studiofarzulla
Zenodo: zenodo.org/communities/farzulla
Web: farzulla.org

All research direction, project selection, funding decisions, and operational matters are determined by Murad Farzulla as the sole researcher and steward of this project. This charter serves as internal governance documentation for the research activity.

Future plans include collaboration with academic institutions, potential integration with doctoral research programs, and contributing to open source security infrastructure at scale. Should collaborators join in the future, governance may be restructured accordingly.