Welcome
to ETIS
In & around
Data Vision
Meet ETIS
ETIS (UMR8051) is a joint research department between CYU Cergy Paris University, ENSEA Graduate School of Electrical Engineering and CNRS Sciences Informatiques.
The department is currently headed by Professor Nistor Grozavu.
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.
Our skills
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.
Meet ETIS
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
Nos labs
Latest publications
- NATE and T-NATE: Efficient transformers for IoT task offloading in edge–fog–cloud computing
- Low Complexity V2V Communication using ISAC FMCW Radar under Clock Impairments
- Tuple Inconsistency Measures: Towards Explaining Query Answers
- On Model Selection for Time to Event Tasks
- Structure from rank: Rank-order coding as a bridge from sequence to structure
- Efficient EV Charging Allocation in Fog Computing via Committee-Based Surrogate-Assisted PSO