Aim and scope:
Future networks will strongly rely on machine learning and artificial intelligence for all kinds of applications, including network control and maintenance, traffic monitoring and analysis, efficient routing, etc. The purpose of this Summer School is to provide students with an up-to-date overview of the main machine learning-based methodologies and applications in the field of networking. Through lectures and keynotes from widely recognized experts in the area, selected from both academia and industry, students will focus on both theoretical and practical aspects of machine learning applied to computer networks. Besides frontal lectures and tutorials, the schedule further comprises one hands-on session, so as to permit the students to gain concrete experience with selected methodologies.
- Pedro Casas [Abstract Available]
Big Data Analytics and Machine Learning for Network Monitoring
Austrian Institute of Technology
- Merouane Debbah [Abstract Available]
Wireless AI: Challenges and Opportunities
Huawei & Centrale Supelec, Paris-Saclay
- Marc Lelarge [Abstract Available]
Hands-on introduction to deep learning with PyTorch
Invited Keynote Talks
- Stefano Basagni
Learning Green Routes: It Pays to be Smart (...but not too Smart!)
Northeastern University, Boston, USA
- Roberto Bifulco
In-network Machine Learning for Networks
NEC Labs Europe, Germany
- Emilio Calvanese Strinati
Exploring Learning Tools for Mobile Edge Computing
CEA LETI, France
- Kaushik Chowdhury
Deep Convolutional Neural Networks for RF Fingerprinting
Northeastern University, Boston, USA
- David Gutierrez Estevez
Artificial Intelligence for 5G Elastic Network Slicing
Samsung Electronics R&D Institute, UK
- Tommaso Melodia
Toward Learning-based Polyglot IoT Platforms
NorthEastern University, Boston, USA
- Diego Perino
A Telco view on AI for Networks: from Backbone to Rural Area Networks
- Alessandro Redondi
Building up Knowledge through Passive Wi-Fi Probes
Politecnico di Milano, Italy
- Vijay Subramanian
Information Design in Social Learning
University of Michigan, Ann Arbor, USA
- Michele Zorzi
Machine Learning at the Edge
University of Padua Italy
The official language is English.
Travel and accomodation
Participants will be arranged in comfortable hotels at very special rates. The conference room (located at Hotel Giardino sul Mare, Via Maddalena, Lipari) is air-conditioned and equipped with all conference materials. Special areas are reserved to students for the afternoon coursework and study. The island of Lipari can be easily reached from Milazzo, Palermo, Naples, Messina and Reggio Calabria by ferry or hydrofoil (50 minutes from Milazzo).
Two kinds of participants are welcome.
Students: Participants who are expected to do afternoon coursework and take a final exam (The grades will be given following the ECTS grading scale). The course will involve a total of 24 hours of teaching. Passing the final exam gives right to an equivalent of 6 ECTS credits in any Ph.D. program.
Auditors: participants who are not interested in taking the final exam.
Registration fees is 500 €. The fee covers the course material, bus+hydrofoil Catania airport-Lipari-Catania airport, social events and coffee breaks. Late registration is 600 €.
Early registration applications can be submitted from February 18th, 2019 up to May 27th, 2019. Late registrations will be accepted until July 2nd, 2019. Admission notification will start on February 18th, 2019, according to registration time. Applicants must include a short curriculum vitae or an updated link to an official website. In case of cancellation after fees payments, a 25% penalty will be applied. In case of credit card payment, processing fees cannot be reimbursed. Payment must be received by May 31st, 2019 for Regular Registration and July 1st, 2019 for Late Registration.
Antonio Capone (Politecnico di Milano, Italy)
Sergio Palazzo (University of Catania, Italy)
Lipari School Permanent Director
School Organizing Committee
Prof. Alfredo Pulvirenti
Prof. Rosalba Giugno
Dr. Salvatore Alaimo
Dr. Giovanni Micale