collaborators

13 papers

math.PR2026

Branching random walk in random environment

Xinxin Chen, Chenlin Gu, Zhiqi Zhao

We consider a branching random walk on \(\Z^d\) in a random environment given by Bernoulli site percolation with parameter \(p\in (0,1)\). In this model, each particle located at a…

eess.SP2026

Retrieval-Based Cross-Domain Generalization in Optical Networks via Global Features

Ali Al Housseini, Carlos Natalino, Paolo Monti +1

We propose a retrieval-based framework for crossdomain quality-of-transmission (QoT) estimation that leverages transferable feature representations while avoiding reliance on sourc…

cs.LG2026

Explanation-Based Runtime Verification for Trustworthy ML-driven Optical Networks

Omran Ayoub, Carlos Natalino, Ali Al Housseini +5

Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, performance monitoring and resource…

cs.NI2026

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning

Ali Al Housseini, Carlos Natalino, Paolo Monti +1

The robustness of machine learning techniques across heterogeneous network domains remains an open challenge in optical networks. Models trained on data from a specific topology or…

cs.NI2026

Human Grounded Evaluation of Large Language Models for Optical Network Automation

Kiarash Rezaei, Omran Ayoub, Paolo Monti +1

Large language models (LLMs) are increasingly adopted for network automation, yet their output quality and inference cost can vary substantially across LLM families. We present HuG…

cs.NI2026

User-Mobility-Aware Optimization of Fiber Placement in Hybrid Fiber-IAB Networks

Piotr Lechowicz, Charitha Madapatha, Carlos Natalino +2

Metaheuristic optimization of hybrid fiber-IAB networks demonstrates that integrating user dynamics into topology design enables more adaptive and cost-efficient backhaul architect…