3rd webinar on “Closed Loop Automation for Networked Systems”

On the 11th of December 2023 14-16.30, AI@EDGE will hold the 3rd webinar of the AI@EDGE webinar series, titled “Closed Loop Automation for Networked Systems“.

In this webinar, we will present a closed-loop automation system making use of AI to automatically mitigate anomalous states of the connect-compute software infrastructure. We will describe different functional blocks of the algorithmic framework, and in particular the anomaly detection module using federated learning, the AI function scheduling to meeting detection performance targets while mitigating AIF stragglers, the data-pipeline system design to ensure high accuracy, real-time data preprocessing and arrival, and a reinforcement learning framework to automatically find reconfiguration intents. The webinar will end with a preliminary demonstration of key system blocks and will highlight further research in this area. 

The webinar will be introduced by Stefano Secci, head of the ROC team, and will be run in hybrid mode: live from Cnam, Paris, France, in room 17.1.14, 292 rue St Martin, and online at this link.

Register at this link: https://forms.gle/uQxu6vp7vjtHeC3LA


14:00 – 14:15Background and Architecture
Nour-El-Houda Yellas
14:15 – 14:35Anomaly Detection AIF (Artificial Intelligence Function) and FL-Based System
Nour-El-Houda Yellas
14:35 – 14:50AIF Placement Optimization
Nour-El-Houda Yellas
14:50 – 15:10Automated Reconfiguration
Naresh Modina
15:10 – 15:40Data Pipelining impact on Detection Performance
Patient Ntumba
15:40 – 16:00 Technical demonstration
Chi-Dung Phung, Salah Bin-Ruba
16:00 – 16:30Questions and discussions 
Moderated by Stefano Secci

Meet our speakers!

Stefano Secci

Stefano Secci is professor at CNAM, Paris, e head of the ROC Team

Nour-El-Houda Yellas

Nour-El-Houda Yellas is a Ph.D. candidate in Cnam, Paris, and teaching assistant at Sorbonne University. She received the master’s degree in network and engineering from Paris Saclay University in 2019. Her Doctoral research concerns mainly the automation and optimization of 5G mobile networks orchestration in multiaccess edge computing infrastructures using data analytics. 

Naresh Modina

Naresh Modina is a Post doctoral candidate at Cnam, he joined ROC team at Cnam (Paris), France on 1st January 2023. He received the M.Sc. degree in telecommunications engineering from Politecnico di Milano, Italy in 2019. He received the PhD in computer science from Avignon University, France in 2022. His current line of research is focused on applying AI in Wireless networks.

Patient Ntumba

Data pipelining system

Patient NTUMBA-WA-NTUMBA is a post-doctoral researcher at Cedric laboratory of Cnam (Paris) in the ROC team. He joined the ROC team in February 2023 where he is carrying out research on data pipelining systems for in-network learning. He received the master’s degree in distributed systems and networks from Université de Franche-Comté (France) in 2017. In 2022, he received the PhD in computer science from Sorbonne University and carried out his doctoral research at INRIA Paris. His research focuses on the Internet of things, data streams, networks, distributed systems, and optimization. 

Chi-Dung Phung

Chi Dung PHUNG is a research engineer at CNAM. Previously, he held research engineering positions at LIP6, UPMC, from 2013 to 2018, and at Orange Lab in 2019. He earned his Ph.D. from UPMC in 2018. His research interests include Internet control protocol design and experimentation. 

Salah Bin-Ruba

Salah Bin-Ruba is a research engineer at CEDRIC lab of CNAM, Paris. He received his M.Sc. in Data Science and Network intelligence from Telecom SudParis in 2020. He is currently working on applying machine learning for anomaly detection in 5G infrastructure. His main research focus is on automation and auto configuration of networks using AI. 

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