178 citations · 270 across the 16 of their papers we have counts for
19 papers
Towards a Unified Multidimensional Explainability Metric: Evaluating Trustworthiness in AI Models
Georgios Makridis, Georgios Fatouros, Athanasios Kiourtis +4
In this paper, we present a comprehensive framework for assessing the explainability of various XAI methods, such as LIME and SHAP, across multiple datasets and machine learning mo…
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…
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…
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…
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…
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…
Towards Conversational AI for Human-Machine Collaborative MLOps
George Fatouros, Georgios Makridis, George Kousiouris +3
This paper presents a Large Language Model (LLM) based conversational agent system designed to enhance human-machine collaboration in Machine Learning Operations (MLOps). We introd…
Bridging Industrial Expertise and XR with LLM-Powered Conversational Agents
Despina Tomkou, George Fatouros, Andreas Andreou +6
This paper introduces a novel integration of Retrieval-Augmented Generation (RAG) enhanced Large Language Models (LLMs) with Extended Reality (XR) technologies to address knowledge…
Self-Explaining Neural Networks for Business Process Monitoring
Shahaf Bassan, Shlomit Gur, Sergey Zeltyn +3
Tasks in Predictive Business Process Monitoring (PBPM), such as Next Activity Prediction, focus on generating useful business predictions from historical case logs. Recently, Deep…
VirtualXAI: A User-Centric Framework for Explainability Assessment Leveraging GPT-Generated Personas
Georgios Makridis, Vasileios Koukos, Georgios Fatouros +1
In today's data-driven era, computational systems generate vast amounts of data that drive the digital transformation of industries, where Artificial Intelligence (AI) plays a key…
XAI for All: Can Large Language Models Simplify Explainable AI?
Philip Mavrepis, Georgios Makridis, Georgios Fatouros +3
The field of Explainable Artificial Intelligence (XAI) often focuses on users with a strong technical background, making it challenging for non-experts to understand XAI methods. T…
Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection
Georgios Fatouros, Konstantinos Metaxas, John Soldatos +1
This paper introduces MarketSenseAI, an innovative framework leveraging GPT-4's advanced reasoning for selecting stocks in financial markets. By integrating Chain of Thought and In…
Enhancing Explainability in Mobility Data Science through a combination of methods
Georgios Makridis, Vasileios Koukos, Georgios Fatouros +1
In the domain of Mobility Data Science, the intricate task of interpreting models trained on trajectory data, and elucidating the spatio-temporal movement of entities, has persiste…
XAI for time-series classification leveraging image highlight methods
Georgios Makridis, Georgios Fatouros, Vasileios Koukos +3
Although much work has been done on explainability in the computer vision and natural language processing (NLP) fields, there is still much work to be done to explain methods appli…
Transforming Sentiment Analysis in the Financial Domain with ChatGPT
Georgios Fatouros, John Soldatos, Kalliopi Kouroumali +2
Financial sentiment analysis plays a crucial role in decoding market trends and guiding strategic trading decisions. Despite the deployment of advanced deep learning techniques and…
Human-Centric Artificial Intelligence Architecture for Industry 5.0 Applications
Jože M. Rožanec, Inna Novalija, Patrik Zajec +17
Human-centricity is the core value behind the evolution of manufacturing towards Industry 5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness,…
PolicyCLOUD: A prototype of a Cloud Serverless Ecosystem for Policy Analytics
Ofer Biran, Oshrit Feder, Yosef Moatti +9
We present PolicyCLOUD, a prototype for an extensible, serverless cloud-based system that supports evidence-based elaboration and analysis of policies. PolicyCLOUD allows flexible…
A Review of Explainable Artificial Intelligence in Manufacturing
Georgios Sofianidis, Jože M. Rožanec, Dunja Mladenić +1
The implementation of Artificial Intelligence (AI) systems in the manufacturing domain enables higher production efficiency, outstanding performance, and safer operations, leveragi…
STARdom: an architecture for trusted and secure human-centered manufacturing systems
Jože M. Rožanec, Patrik Zajec, Klemen Kenda +14
There is a lack of a single architecture specification that addresses the needs of trusted and secure Artificial Intelligence systems with humans in the loop, such as human-centere…