About me

I currently hold an Associate Professor position in Computer Science at EFREI Paris.

I obtained my PhD in Computer Science from the University of Bordeaux (France) in October 2016 (advisors: Arnaud Casteigts, Serge Chaumette and Colette Johnen). I then held a Teaching and Research Associate position at INP ENSEIRB-MATMECA (teaching institution) and LaBRI (Bordeaux CS dept.), and at INSA Toulouse (national institute of applied sciences) and LAAS-CNRS (Laboratory for Analysis and Architecture of Systems). I am mainly interested in dynamic networks and distributed algorithms.

Current affiliation:

Teaching institution: EFREI Paris - École Française d'Éléctronique et d'Informatique

Laboratory: AlliansTIC

Research group: Objets connectés

Past affiliation :

2017 - 2018

Teaching institution: INSA-Toulouse

Laboratory: LAAS-CNRS - Laboratory for Analysis and Architecture of Systems

Research group: SARA - Services and Architectures for Advanced Networks

2017

Laboratory: IRIT - Toulouse Institute of Computer Science Research

Research group: SMAC - Cooperative Multi-Agent Systems

2013 - 2017

Teaching institution: Bordeaux INP ENSEIRB-MATMECA

Laboratory: LaBRI - Bordeaux Computer Science Research Laboratory

Research groups: Distributed computing & COMET - COntext-aware Management of mEdia and neTworks

Research interests

I am currently working within the SARA team at the LAAS-CNRS lab on dynamic network analysis and modeling, with the aim to understand what really characterizes these networks.

I am interested, more generally, in dynamic graphs and distributed algorithms in dynamic networks. Dynamic networks consist of entities making contact over time with one another. A major challenge in dynamic networks is to predict dynamics patterns and decide whether the evolution of the topology satisfies requirements for the success of given algorithms. The types of dynamics resulting from these networks are varied in scale and nature. For instance, some of these networks remain connected at all times; others are always disconnected but still offer some kind of connectivity over time and space (temporal connectivity); others are recurrently connected, periodic,etc. All of these contexts can be represented as dynamic graph classes corresponding to necessary or sufficient conditions for given distributed problems or algorithms. Given a dynamic graph, a natural question to ask is to which of the classes this graph belongs. I mainly worked on the automation of dynamic graphs classification, proposing strategies for dynamic graph analysis, and developing frameworks and algorithms for testing relevant properties and computing parameters in dynamic graphs. I also attempt to understand what can still be done in a context where no property on the network is guaranteed and no assumption on the evolution of the network dynamics is made through the study of distributed problems.

The manuscript of my thesis is available locally [pdf] and on the online library of the University of Bordeaux [pdf].

The slides used during my defense are also available [pdf].

Contact

Email: yessin.neggaz@efrei.fr

EFREI-Paris

30-32, Av. de la République

94800 Villejuif France