works on

From the 1 of 9 linked papers with an AI index.

most citedTowards a Unified Multidimensional Explainability Metric: Evaluating Trustworthiness in AI Models

8 citations · 8 across the 1 of their papers we have counts for

collaborators

9 papers

cs.LG20268 cited

Towards a Unified Multidimensional Explainability Metric: Evaluating Trustworthiness in AI Models

Georgios Makridis, Georgios Fatouros, Athanasios Kiourtis +4

The paper proposes a framework that evaluates explainability methods like LIME and SHAP across models and datasets using fidelity, simplicity, and stability, and builds a knowledge…

cs.CR2026

An Organization-Scoped LLM Agent Runtime Architecture for Regulated Cybersecurity Operations

George Fatouros, Georgios Makridis, George Kousiouris +2

Regulated cybersecurity workflows lack a runtime substrate that enforces organization-level scope across retrieval, tool calls, memory, findings, reports, and audit while remaining…

cs.AI2026

Persistent and Conversational Multi-Method Explainability for Trustworthy Financial AI

Georgios Makridis, Georgios Fatouros, John Soldatos +2

Financial institutions increasingly require AI explanations that are persistent, cross-validated across methods, and conversationally accessible to human decision-makers. We presen…

cs.AI2026

Native Explainability for Bayesian Confidence Propagation Neural Networks: A Framework for Trusted Brain-Like AI

Georgios Makridis, Georgios Fatouros, John Soldatos +2

The EU Artificial Intelligence Act (Regulation 2024/1689), fully applicable to high-risk systems from August 2026, creates urgent demand for AI architectures that are simultaneousl…

cs.AI2026

CyberAId: AI-Driven Cybersecurity for Financial Service Providers

George Fatouros, Georgios Makridis, John Soldatos +18

European financial institutions face mounting regulatory pressure while their security operations centres remain constrained not by data or staffing but by reasoning capacity: ente…

cs.HC2025

HumAIne-Chatbot: Real-Time Personalized Conversational AI via Reinforcement Learning

Georgios Makridis, George Fragiadakis, Jorge Oliveira +4

Current conversational AI systems often provide generic, one-size-fits-all interactions that overlook individual user characteristics and lack adaptive dialogue management. To addr…