Research Days 2021

October 11 – 12, 2021

Once a year, Labex DigiCosme (Digital Worlds) presents its research topics and results: software security and reliability, cryptography, cyber-physical systems, formal methods, smart networks, internet of things, smart cities, data science, deep learning, text mining, artificial intelligence.

Program

Monday, 11th October , 2021

  • 9:30 – 9:45: Opening session
  • 9:45 – 10:45: Keynote talk – Pierre-Yves Strub
  • 10:45 – 11:15: Coffee break
  • 11:15 – 12:15: PhD presentations
    • Amélie Ledein – Scilex
    • Anfu Tang – IID
    • Loric Duhaze – Scilex
  • 12:15 – 14:00: Lunch break
  • 14:00 – 15:00: Keynote talk – Catherine Rosenberg
  • 15:00 – 15:30: Presentation of the graduate schools
    • Franck Richecoeur
    • Nicolas Sabouret
  • 15:30 – 16:00: Pitch poster of the master students
  • 16:00 – 17:00 : Coffee break + poster exposition

Tuesday, 12th October , 2021

  • 9:30 – 10:30 : Keynote talk – Elisa Fromont
  • 10 :30 – 11:00 : Hot topics presentation
  • 11:00 – 11:30 : Coffee break
  • 11:30 – 12:30: PhD presentations
    • Fakher Sagheer – Comex
    • Angelo Saadeh – Scilex Comex
    • Felipe Lisboa – Scilex
  • 12:30 – 14:00 Lunch break
  • 14:00 – 14:30 : Presentation —
  • 14:30 – 15:00: Initiatives transverses presentations
    • NewEMMA
    • STARS
  • 15:00 – 15:40 : PhD presentations
    • Gian Karlo Aguirre-Samboni – Scilex
    • Jialin Hao – Comex IID
  • 15:40 – 16:10 : Perspectives of the Labex

Keynote talks

  • Elisa Fromont, Centre de recherche IRISA, “Explicabilité pour la Classification de Séries Temporelles”

Après avoir brièvement redonné les motivations inhérentes à l’explication des méthodes d’apprentissage automatique en général et d’apprentissage profond en particulier; ainsi qu’un état de l’art des méthodes actuelles, je proposerais quelques contributions que mes étudiants et moi avons pu avoir sur le sujet, notamment pour pour la classification de séries temporelles univariées et multivariées (Adversarial Regularization for Explainable-by-Design Time Series Classification – ICTAI 2020; A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers – IJCAI Workshop on Explainable Artificial Intelligence (XAI), 2020; XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification. CoRR abs/2009.04796 (2020))

Abstract: A brief overview of 5G followed by a discussion on where 5G research is going. She will share her experience working on 5G with industry and operators in Canada and in France and conclude by a short description of what is emerging as the early concepts behind 6G.

Bio: Catherine Rosenberg is a Professor in Electrical and Computer Engineering at the University of Waterloo since 2004. Since June 2010, she holds the  Canada Research Chair in the Future Internet. She was elected an IEEE Fellow for contributions to resource management in wireless and satellite networks in 2011 and was elected a Fellow of the Canadian Academy of Engineering in 2013. In April 2018, she became the Cisco Research Chair in 5G Systems. Part of her career was in industry, in Alcatel in France, in AT&T Bell Labs in the USA and in Nortel Networks in the UK. She held faculty positions in Ecole Polytechnique, Montreal and Purdue university. Her research expertise lies in wireless networks, multimedia, traffic engineering and energy systems.

  • Pierre-Yves Strub, École Polytechnique, LIX (Laboratoire d’Informatique de l’X), “High-Assurance and High-Speed Cryptographic Implementations