We got a deep dive into some of the most memorable moments of 2022.
Continue readingIEEE Big Data 2022: the key takeaways
In December 2022, our research director Sabri Skhiri travelled to Osaka to attend IEEE Big Data 2022. He sums up the main trends, and shares his favourite talks and papers.
Continue readingDynamic Pairwise Wake Vortex Separations For Arrivals Using Predictive Machine Learning Models
Aircraft wake behaviour and meteorological information is monitored and processed using ML algorithms which determine the wake separation minimum reductions that can be safely applied between subsequent arriving aircraft.
Continue readingIntelligent Data Integration for Complex Problem Solving
Internships 2023
This document presents internships supervised by our software engineering department or by our research & development department. Each project is an opportunity to feel both empowered and responsible for your own professional development and for your contribution to the company.
Continue readingAI For Aviation
Our team works with EUROCONTROL and WaPT to safely reduce wake separation between flights. Read on to read more about the two papers they recently published!
Continue readingIEEE Streaming Workshop / Keynote Announcement
We are delighted to announce Pablo Estrada from Google and Fabian Hueske from Snowflake as the two keynote speakers of our seventh Workshop on Real-time Stream Analytics, Stream Mining, CER/CEP & Stream Data Management in Big Data.
Continue readingWe Collaborate on the TAUDoS Project
We started a new collaboration with Aix-Marseille University, Montreal University, Nantes University, and St-Etienne on a four-year project called TAUDoS, which focuses on Trustful AI.
Continue readingDEBS 2022
In June 2022, our research director Sabri Skhiri and the head of the data science department Madalina Ciortan travelled to Copenhagen to attend DEBS 2022, the leading conference focusing on distributed and event-based systems.
Continue readingCalibrate to Interpret
Trustworthy machine learning is driving a large number of the ML community works in order to improve ML acceptance and adoption. In this paper, we show a first link between uncertainty and explainability, by studying the relation between calibration and interpretation.
Continue reading