IMT Atlantique is particularly involved in the national doctoral programme on artificial intelligence led by the Institut Mines-Télécom, called AI@IMT. Out of the first 10 thesis topics selected for 2022, IMT Atlantique is working on 7 in high-stake areas: security, health, the industry of the future, and the data economy.
The AI@IMT doctoral programme
Improving research on artificial intelligence by involving more PhD students in new or existing projects; encouraging research on AI with a particular focus on the digital transition, the energy transition, the industry of the future, and connected health; developing research partnerships to meet the needs of industry and society -- These are all national strategic imperatives that this AI@IMT PhD programme intends to address.
AI@IMT involves 50% ANR (French National Research Agency) funding for of 20 theses within the framework of the national AI research programme, which makes it one of the largest programmes funded within this framework. The first 10 topics were selected by the steering committee, composed of 4 academics and 4 private research actors.
AI@IMT also involves the participation of the Institut Mines-Télécom Business School, Mines Saint-Étienne and IMT Nord Europe, as well as TeraLab, an acceleration platform for research, innovation and education in AI and Big Data.
The proposed theses
- Machine Learning and Matheuristics algorithms for urban transportation
Romain Billot (IMT Atlantique)
- Human gestural analysis based on finegrained motion and graph convolutional networks
Hazem Wannous (IMT Nord Europe)
- Training Deep Neural Networks using unreliable hardware
Vincent Gripon (IMT Atlantique)
- Joint design of compression techniques for deep neural networks and low-energy processors for event-based computer vision
Matthieu Arzel (IMT Atlantique)
- Simplification of energy network models through AI
Patrick Meyer, Bruno Lacarrière (IMT Atlantique)
- Contraints Programming and model learning in Stable Matching
Gilles Simonin (IMT Atlantique)
- Abductive Reasoning with Minimal Sensing in a Home Environment
Antoine Zimmermann (Mines Saint-Étienne)
- Unknown Input Observers for an efficient management of hydrographical networks based on Predictive Control
Gilles Belaud, Eric Duviella (IMT Nord Europe)
- Counting and sampling of solutions for anytime pattern discovery
Samir Loudni (IMT Atlantique)
- Distributed learning on connected devices
Amer Baghdadi (IMT Atlantique)
Application deadline: 10 May 2022
by Pierre-Hervé VAILLANT