Carlos Natalino Da Silva
Carlos Natalino is a postdoc with the Optical Networks Unit, focusing on the application of machine learning to telecommunication infrastructure problems. Among the main topics are the design and management of optical networks and cloud computing infrastructures, with special focus on resource and energy efficiency, security, reliability and survivability. He has been involved in several national and international projects funded by research bodies in EU and Brazil. He has also been involved in teaching computer programming courses in Brazil and Sweden. He is an IEEE member.
Showing 36 publications
Microservice-Based Unsupervised Anomaly Detection Loop for Optical Networks
Feedforward Neural Network-Based EVM Estimation: Impairment Tolerance in Coherent Optical Systems
Fast signal quality monitoring for coherent communications enabled by CNN-based EVM estimation
Spectrum Anomaly Detection for Optical Network Monitoring using Deep Unsupervised Learning
Deep Learning Assisted Pre-Carrier Phase Recovery EVM Estimation for Coherent Transmission Systems
Storage Protection with Connectivity and Processing Restoration for Survivable Cloud Services
Network automation: challenges, enablers, and benefits
A GPU-assisted NFV framework for intrusion detection system
Autonomous Security Management in Optical Networks
Scalable Physical Layer Security Components for Microservice-Based Optical SDN Controllers
Design of Programmable Filterless Optical Networks
Root Cause Analysis for Autonomous Optical Networks: A Physical Layer Security Use Case
A Heuristic Approach for the Design of UAV-Based Disaster Relief in Optical Metro Networks
Machine Learning for Optical Network Security Monitoring: A Practical Perspective
Forecasting power load curves from spatial and temporal mobile data
Network Slicing Automation: Challenges and Benefits
Content placement in 5G‐enabled edge/core datacenter networks resilient to link cut attacks
Machine Learning for Optical Network Security Management
The Optical RL-Gym: an open-source toolkit for applying reinforcement learning in optical networks
Machine Learning for Cognitive Optical Network Security Management
Network-wide localization of optical-layer attacks
Availability-Guaranteed Service Function Chain Provisioning with Optional Shared Backups
Machine Learning Methods for Slice Admission in 5G Networks
One-Shot Learning for Modulation Format Identification in Evolving Optical Networks
Demonstration of Machine-Learning-Assisted Security Monitoring in Optical Networks
Enhancing optical network security with machine learning
Reinforcement Learning for Slicing in a 5G Flexible RAN
Cost Benefits of Centralizing Service Processing in 5G Network Infrastructures
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Showing 4 research projects
Secured autonomic traffic management for a Tera of SDN flows (TeraFlow)
Automation of Network edge Infrastructure & Applications with aRtificiAl intelligence, ANIARA
Smart City Concepts in Curitiba - low-carbon transport and mobility in a digital society