the AI revolution
In & around
ETIS is a joint research department between CYU Cergy Paris University, ENSEA Graduate School of Electrical Engineering and CNRS/INS2I. The department is currently headed by Prof. Olivier Romain assisted by Prof. Lola Canamero.
ETIS develops research in the field of the theory of information with both theoretical and experimental activities in order to allow information processing systems to acquire capacities of autonomy. Autonomy is considered both in terms of learning and adaptation to the environment (including users) as well as making decision that includes low energy consumption and computing power for example.
ETIS designed systems perform intelligent processing which is adaptable to increasing complexity. The concerned areas are reconfigurable chip systems, data analysis, image indexing, developmental robotics, information theory and telecommunications. Learning and adaptation algorithms based on data constitue the core of the developed systems.
The ETIS laboratory is at the heart of the current AI revolutionLearning and adaptation algorithms based on data constitue the core of the developed systems.
In this sense, the ETIS laboratory is at the heart of the current AI revolution.
Learning and optimization
Bioinspired cognitive modelling, Cognitive robotics, ML for computer vision, Green telecommunication systems, Information and game theory.
Large scale smart processing
Data mining for social network, Cultural heritage sciences, life sciences and medicine , Distributed telecommunication network.
Smart Embedded Systems
Analog and digital electronics, Autonomous systems, Low foot print systems, Embedded systems for life science.
ETIS engineering division aims to better sharing expertise by developing projects of engineering as well as by practicing research technology transfer.
Actions of the engineering division include: training and sharing of experiences in the form of open presentations to the entire laboratory and project support or development.
Skilled Engineered Highlighted & Equipped
Indexing, analysis and research of visual content
Smart Embedded Systems
Modelling of Learning
Multimedia Indexing & Data Integration
- Integrated neuro-robotic approaches for autonomous vehicle localisation and navigation
- Machine Learning-based Robust Physical Layer Authentication Using Angle of Arrival Estimation
- Deep Reinforcement Learning-Based Network Slicing Algorithm for 5G Heterogenous Services
- Wing Interferential Patterns (WIPs) and machine learning for the classification of some Aedes species of medical interest
- Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species
- Novel Slice Admission Control Scheme with Overbooking and Dynamic Buyback Process