Academia Program · Cognitive Logic · Bologna 2026

Research
Infrastructure
for Ethical AI

Cognitive Logic opens its QEN framework, scoring datasets and agent architecture to universities, PhD candidates and independent researchers. Formal collaborations, open data tracks, joint publication pathways.

QEN Dataset PhD Track Thesis Supervision EU AI Act Research CSRD Measurement Bolkestein 2027 Territorial Economics

Verticals

40+

QEN variables

Pilot datasets

Open

Access track

Research Domains

What you can study
with QEN

The QEN framework produces structured, multi-dimensional ethical scores anchored to verifiable regulatory obligations. Four primary research domains.

Domain 01

Ethical AI Measurement & Scoring

Quantitative methodologies for encoding social, environmental and territorial values into machine-readable scores. Weighting models, uncertainty propagation, multi-stakeholder aggregation.

QEN Score EU AI Act Annex III GDPR Art.22 Explainability

Domain 02

CSRD & Non-Financial Disclosure

Operationalising CSRD sustainability reporting for SMEs and micro-operators. Green Claims Directive compliance, double materiality assessment, automated evidence extraction from unstructured documents.

CSRD Green Claims ESRS SME reporting

Domain 03

Territorial Intelligence & Local Economics

Proximity supply chains, Km0 sourcing networks, place-based economic rootedness indicators. Intersection of territorial data with regulatory compliance in the HoReCa and coastal tourism sectors.

Territorial score Vt Bolkestein 2027 Concessions HoReCa

Domain 04

Autonomous Agent Governance

Multi-agent orchestration patterns for regulatory compliance workflows. LLM-based auditing agents, escalation logic, human-in-the-loop design under EU AI Act high-risk system constraints.

Agent architecture EU AI Act Annex I GDPR Art.35 DPIA Oversight

QEN Framework

The scoring formula

QEN (Quantum Ethics Network) quantifies enterprise ethical performance across three orthogonal dimensions. The formula is fully open for academic inspection and critique.

QEN v1.0 — Primary aggregation formula

QEN = Vs × 0.40 + Va × 0.35 + Vt × 0.25

Social Score

weight 0.40

Labour conditions, worker welfare, community impact, gender equity, supply chain human rights.

Environmental Score

weight 0.35

Carbon footprint, waste management, energy sourcing, biodiversity impact, CSRD materiality.

Territorial Score

weight 0.25

Local sourcing (Km0), territorial rootedness, cultural heritage, place-based economic contribution.

All three dimensions are scored 0–100. The output QEN score is likewise 0–100. Full variable definitions, sub-indicator lists and weighting justification are documented in the Methodology v1.0.

Collaboration Tracks

How we work together

Three structured pathways for academic engagement. All tracks are formalized via a brief research protocol submission.

Track A

Thesis & Dissertation

Bachelor, Master and PhD theses directly using QEN data or methodology. Cognitive Logic provides dataset access, methodology documentation, and technical support sessions.

Dataset access (anonymized, structured)
Methodology consultation (3 sessions)
Co-authorship on outputs negotiable
Certificate of collaboration issued
Duration: semester to academic year

Track B

Joint Research & Publication

Collaborative research projects aimed at peer-reviewed publication. Focus areas: ethical AI measurement, CSRD operationalisation, territorial economics, autonomous agent governance.

Full dataset access (non-anonymized on NDA)
Roberto Malini co-authorship
Shared attribution on methodological IP
Target: conference papers + journal submissions
Duration: 6–18 months

Track C

Research Consultancy

External advisory role for research groups needing applied compliance expertise. Regulatory interpretation, framework validation, field data access via Cognitive Logic operator network.

Advisory sessions (4–8 per project)
Access to live operator data (NDA required)
EU funding proposal support (Horizon, EIC)
No co-authorship required
Compensation: negotiable / pro-bono for PhD candidates

Data Access

Available datasets

Structured datasets produced through the Cognitive Logic pilot program. Covering Bologna HoReCa operators, coastal concessions and food supply chains.

Dataset	Vertical	Records	Variables	Access
QEN-RIST-BO-2026 Bologna restaurants — pilot cohort	Ristorazione	5 operators	38 variables	On request
QEN-BALNEARI-2026 Coastal concessions — Bolkestein compliance	Balneare	Expanding	42 variables	On request
QEN-HORECA-SYNTHETIC Synthetic benchmark dataset for methodology testing	HoReCa	100 synthetic	40 variables	Open
COMPLIANCE-VECTORS-EU Regulatory text embeddings — EU AI Act, CSRD, GDPR	Regulatory	Structured corpus	NLP vectors	Open
QEN-ALBERGHIERO-2026 Hotel & accommodation — seasonal operators	Alberghiero	Planned Q4 2026	~44 variables	Q4 2026

All datasets requiring access are gated by a brief research protocol form and NDA where applicable. Anonymized versions of pilot data are available immediately upon track enrollment.

Publications & Working Papers

Research outputs

Working papers, methodology documents and forthcoming submissions from the Cognitive Logic research program.

Working Paper · 2026 · v1.0

QEN Score: A Multi-Dimensional Ethical Scoring Framework for SME Compliance in EU Regulatory Contexts

Roberto Malini — Cognitive Logic, Bologna

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Technical Note · 2026

Autonomous Agent Architectures for Regulatory Compliance: EU AI Act High-Risk Classification and Oversight Patterns

Roberto Malini — Cognitive Logic, Bologna

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Forthcoming · Target: Q3 2026

Bolkestein Directive 2027 and the Measurement of Territorial Rootedness: A Scoring Approach for Italian Coastal Concessions

Roberto Malini · Open for co-authorship

Join →

Planned · 2026–2027

CSRD Operationalisation for Micro-Operators: Automated Evidence Extraction and Double Materiality Assessment at Scale

Open collaboration — seeking university partner

Propose →

Start a collaboration

Send a two-paragraph research protocol: your institution and role, the research question you want to address, which dataset or framework component you need. We respond within 5 working days. PhD candidates and under-resourced institutions: pro-bono access available.

Apply via email Read methodology