You may have realized while browsing our site (at least we hope so), we are tech-savyy and we want to be a TRUE partner in our ecosystem. For this, we have chosen to invest heavily in the field of research.

So how do we do it ?

We have defined a process allowing us to bring out the themes that we want to develop and therefore in which we invest.

There are 4 of these today.


Ours projects are managed by several heads of missions under the coordination of an R&D director and in partnership with 4 research laboratories located in France. They are initiated on the basis of monitoring studies conducted by our observatories.

Some examples of publications :

  • Modeling and performance evaluation of the eICIC/ABS in H-CRAN, Cores 2018, Roscoff : Touati H, Castel-Taleb H, Jouaber B, Akberzadeh S, Khlass A.
  • A two-stage algorithm for the virtual embedding problem, Conference on Local Computer Networks (LCN) 2021, Massinissa Ait Aba, Maxime Elkael, Badii Jouaber, Hind Castel-Taleb, Anrea Araldo et David Olivier.
  • Can We Spot Energy Regression using Developers Tests?, Registered Report Track, 37th International Conference on Software Maintenance and Evolution (ICSME’21):  Benjamin Danglot, Jean-Rémy Falleri et Romain Rouvoy.

 

And interventions:

Davidson consulting has been supporting the development of the “Digital Inventivities” Chair since 2019, the first teaching chair dedicated to digital creativity, carried by Institut Mines-Télécom Business School, in partnership with Télécom SudParis and ESAD de Reims, with the support SIANA, CUBE and the Mines-Télécom Foundation.

The objective of the Chair is to create innovative educational tools for the former managers of tomorrow to master creativity techniques in a digital context. Davidson is also supporting the development of the MooC “Creative Thinking: managing digital creativity.

https://www.imt-bs.eu/recherche/chaires/inventivites-digitales/

Patents :

  • FR3023031 : method of identifying a movement by quantified recursive
  • FR3023032 : method of identifying a movement by reducing the number of possible transitions
  • FR3023033 : method of identifying a movement by minimizing the energy of paths
  • FR3023034 : method of identifying a movement by minimizing a functional
  • FR3023035 : method of identifying a movement by simplification of the hidden Markov Model
  • FR3077148 : method and electronic device for selecting at least one message from a set of several messages, associated computer program