collaborators

5 papers

cs.LG2026

Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting

Amirhossein Ghaffari, Saeid Sheikhi, Ekaterina Gilman

Spatio-temporal forecasting on sensor graphs is commonly tackled with a single backbone architecture applied uniformly across all nodes, although graph regions can exhibit differen…

cs.CR2026

ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks

Saeid Sheikhi, Panos Kostakos, Lauri Loven

Intrusion detection systems (IDSs) for 5G networks must handle complex, high-volume traffic. Although opaque "black-box" models can achieve high accuracy, their lack of transparenc…

cs.AI2026

Chain of Simulation: A Dual-Mode Reasoning Framework for Large Language Models with Dynamic Problem Routing

Saeid Sheikhi

We present Chain of Simulation (CoS), a novel dual-mode reasoning framework that dynamically routes problems to specialized reasoning strategies in Large Language Models (LLMs). Un…

cs.CR2025

Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments

Saeid Sheikhi, Panos Kostakos, Lauri Loven

Federated Learning (FL) in 5G and edge network environments face severe security threats from adversarial clients. Malicious participants can perform label flipping, inject backdoo…

cs.HC2025

An Empirical Evaluation of AI-Powered Non-Player Characters' Perceived Realism and Performance in Virtual Reality Environments

Mikko Korkiakoski, Saeid Sheikhi, Jesper Nyman +3

Advancements in artificial intelligence (AI) have significantly enhanced the realism and interactivity of non-player characters (NPCs) in virtual reality (VR), creating more engagi…