IEEE Big Data 2025: the shift from scale to smart
IEEE Big Data 2025 signals a shift to secure, hybrid intelligence. CTO Sabri Skhiri unpacks the engineering reality from the conference: the practical shift to embeddings, the real need for security layers, and the limitations of AI agents in production.
Evaluation of GraphRAG Strategies for Efficient Information Retrieval
Traditional RAG systems struggle to capture relationships and cross-references between different sources unless explicitly mentioned. This challenge is common in real-world scenarios, where information is often distributed and interlinked, making graphs a more effective representation. Our work provides a technical contribution through a comparative evaluation of retrieval strategies within GraphRAG.
Flight Load Factor Predictions based on Analysis of Ticket Prices and other Factors
The ability to forecast traffic and to size the operation accordingly is a determining factor, for airports. However, to realise its full potential, it needs to be considered as part of a holistic approach, closely linked to airport planning and operations. To ensure airport resources are used efficiently, accurate information about passenger numbers and their effects on the operation is essential. Therefore, this study explores machine learning capabilities enabling predictions of aircraft load factors.
Beyond the cloud, advanced AI computer vision
From Cloud to Edge: how to transform your business model with Edge AI? Dive into embedded computer vision and edge AI algorithm development with STMicroelectronics STM32 and Euranova.
Investigating a Feature Unlearning Bias Mitigation Technique for Cancer-type Bias in AutoPet Dataset
We proposed a feature unlearning technique to reduce cancer-type bias, which improved segmentation accuracy while promoting fairness across sub-groups, even with limited data.
Muppet: A Modular and Constructive Decomposition for Perturbation-based Explanation Methods
The topic of explainable AI has recently received attention driven by a growing awareness of the need for transparent and accountable AI. In this paper, we propose a novel methodology to decompose any state-of-the-art perturbation-based explainability approach into four blocks. In addition, we provide Muppet: an open-source Python library for explainable AI.
AI-assisted coding without process is just chaos
Teams ship AI-generated code faster than ever — and accumulate debt just as fast. The problem isn't the tools. It's the missing process around them.
From data governance to GenAI: strategic insights from Warsaw Tech Summit 2025
This year, one of the biggest technological conferences in Central Europe changed its name to Data & AI Warsaw Tech Summit to reflect the latest technological advancements. Our CTO Sabri Skhiri was on the ground to bring back insights.
Development & Evaluation of Automated Tumour Monitoring by Image Registration Based on 3D (PET/CT) Images
Tumor tracking in PET/CT is essential for monitoring cancer progression and guiding treatment strategies. Traditionally, nuclear physicians manually track tumors, focusing on the five largest ones (PERCIST criteria), which is both time-consuming and imprecise. Automated tumor tracking can allow matching of the numerous metastatic lesions across scans, enhancing tumor change monitoring.
Tech insights from Data & AI Tech Summit Warsaw 2025
11 editions later, one of the biggest technological conferences in Central Europe changed its name to reflect the latest technological advancements. Our CTO, Sabri Skhiri, was present to gather the insights. Here’s a rundown of the key trends, keynotes and talks that took place.
Unlocking the power of unsupervised learning with interpretable graph embeddings
Unsupervised learning offers immense potential, but deciphering the results is often a challenge. Discover INGENIOUS, a groundbreaking framework from Euranova that generates interpretable graph embeddings that reveal the 'why' behind complex data patterns, empowering organizations to make informed decisions with confidence.
Data driven- IT operations in banking
A Belgian bank sought to become data‑driven by unifying fragmented IT data, automating reporting, and building secure pipelines to deliver reliable KPIs, faster decisions, and GDPR‑compliant insights across its IT operations.
Edge AI engineering: Euranova’s partnership with STMicroelectronics
This partnership focuses on the technical integration of machine learning models into constrained embedded environments. We provide the architectural rigor required to deploy low-latency, high-throughput AI directly onto STMicroelectronics silicon.
Enhancing productivity and security with computer vision
A leading Belgian food retailer sought to ease warehouse congestion by using computer vision to guide forklift drivers in real time, reducing picker‑driver interference to boost productivity and safety.
Euranova. Implémenter des solutions technologiques qui n’existent pas encore.
Comment savoir quelles technologies utiliser, implémenter, voire créer de toute pièce afin de répondre aux besoins très spécifiques, voire uniques de certaines entreprises?
Construire une culture d’entreprise innovante, inclusive et dynamique
Dans ce nouvel épisode du podcast "Les portraits de l'IA", Maryse Colson, responsable du people office chez Euranova, intervient pour échanger sur la culture d'entreprise et la diversité dans le secteur de l'intelligeance artificielle.
Euranova France is Flying Drones: Find Out Why
Learn about the innovative applications, challenges, and solutions in computer vision, and dive into case studies with us!
Exploring the future of data and AI
Our CTO, Sabri Skhiri, recently travelled to Sorrento for IEEE Big Data 2023. He explores for you the various keynotes and talks that took place during the conference, highlighting the noteworthy insights and the practical applications shared by industry leaders.
Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings
In this paper, we study graph representation learning and show that data augmentation that preserves semantics can be learned and used to produce interpretations. Our framework, which we named INGENIOUS, creates inherently interpretable embeddings and eliminates the need for costly additional post-hoc analysis.
Static FAQ replaced by smart chatbot
A Belgian telecom provider wanted to cut support calls by replacing its static FAQ with a scalable RAG‑powered chatbot that delivers accurate, immediate answers through a simple search‑based interface.
SANGEA: Scalable and Attributed Network Generation
In this paper, we present SANGEA, a sizeable synthetic graph generation framework that extends the applicability of any SGG to large graphs. By first splitting the large graph into communities, SANGEA trains one SGG per community, then links the community graphs back together to create a synthetic large graph.
Explore the nuances of the European AI Act
This conversation offers an in-depth examination of the #EuropeanAIAct and its potential impact on the world for ethical AI. An important discussion with Maria Leitão Marques, Member of the European Parliament; Bianca Manelli, Officer for AI and Data Policy at Digital Europe; Eric Delacroix, Partner at Euranova and Daniela Braga, founder and CEO of Defined.AI.
Euranova et l’Institut Carnot CALYM s’associent pour améliorer la découverte de biomarqueurs grâce à l'IA
Le centre privé de recherche et développement (R&D) Euranova, spécialisé dans la science des données et l’IA, et l’Institut Carnot CALYM annoncent une collaboration avec le soutien institutionnel de Roche pour faire avancer la recherche clinique en imagerie médicale, qui se concentrera sur le lymphome folliculaire.
Turning an intranet into an AI assistant
Sales and support agents can’t live without it : MAiA turns Proximus’ intranet into realtime knowledge, cutting search time and powering 1.4 million questions since launch.