Track 1 🧠
Advanced AI, Machine Learning & Cognitive Intelligence
This track explores the frontiers of artificial intelligence and machine learning — from foundational models and cognitive architectures to responsible, deployable intelligent systems that reason, learn and adapt. It bridges theoretical advances with real-world applications across medicine, finance, robotics and beyond.
🤖 Deep Learning⚡ AutoML🔍 XAI🌐 Multi-Agent🧬 Foundation Models🔄 Transfer Learning
MB
Mohamed Amine BOUDIA
Université Polytechnique Hauts-de-France 🇫🇷
TBC
Chair — To Be Confirmed
International University 🌍
- Deep Learning & Neural Architectures
- Generative AI & Foundation Models
- Explainable AI (XAI) & Interpretability
- Reinforcement & Transfer Learning
- AutoML & Neural Architecture Search
- Federated & Continual Learning
- Multi-Agent Systems & Swarm Intelligence
- Cognitive Computing & Brain-Inspired AI
- AI for Scientific Discovery
- Edge AI & On-Device Intelligence
- AI Ethics & Responsible AI
- Large Language Models & Applications
Track 2 📊
Data Science, Knowledge & Information Systems
Covering the full data intelligence stack — from raw data engineering to knowledge representation and decision-support systems — this track addresses the challenges of volume, variety, velocity and veracity in modern information ecosystems, enabling smarter, data-driven decisions at scale.
📦 Big Data🕸️ Semantic Web🔎 Information Retrieval💡 Knowledge Graphs📈 Data Mining🔗 Linked Data
AR
Pr. Amjad Rattrout
Arab American Univ., Jenin 🇵🇸
KB
Pr. Khalid Ben Abdeslam
LIRIS Laboratory, Lyon 🇫🇷
- Big Data Engineering & Analytics
- Ontologies & Semantic Web Technologies
- Knowledge Graphs & Representation
- Information Retrieval & Recommender Systems
- Data Mining & Pattern Recognition
- Data Integration & Interoperability
- Linked Open Data & Web of Data
- Business Intelligence & Decision Support
- Real-Time Stream Processing
- Open & FAIR Data Principles
- Data Quality & Governance
- Natural Language Processing & Text Mining
Track 3 🔐
Secure Distributed & Trustworthy Computing
As computation migrates to distributed, cloud and edge environments, ensuring reliability, privacy and trust becomes paramount. This track addresses the convergence of security engineering, cryptographic protocols and decentralised architectures that underpin next-generation trustworthy systems.
☁️ Cloud Security⛓️ Blockchain🔒 Privacy🌿 Edge Computing🔑 Cryptography🛡️ Zero-Trust
ZT
Zakaria TBATOU
Abdelmalek Essaadi University 🇲🇦
TBC
Chair — To Be Confirmed
International University 🌍
- Cloud, Edge & Fog Computing Security
- Blockchain & Decentralised Protocols
- Privacy-Preserving Computation
- Zero-Trust & Micro-Segmentation Architectures
- Intrusion Detection & Threat Intelligence
- Cryptography & Post-Quantum Security
- Secure Multi-Party Computation
- Trust Management & Identity Federation
- Distributed Ledger Technologies
- Reliability, Resilience & Fault Tolerance
- Secure Software Engineering
- Formal Verification & Security Proofs
Track 4 🛡️
AI-Driven Cybersecurity & Resilient Intelligence for IoT Ecosystems
The explosion of connected IoT devices creates an ever-expanding attack surface. This track focuses on AI-powered defensive mechanisms, resilient architectures and intelligent monitoring frameworks that protect complex IoT ecosystems from evolving cyber threats, combining machine intelligence with robust system design.
🔍 Threat AI📡 IoT🧩 Federated Security🧬 Digital Twin🤖 SOAR🛰️ 5G/6G
ZH
Dr. Zineb Hidila
LPRI-EMSI Casablanca 🇲🇦
FM
Pr. Fabrice Monteiro
Lorraine University 🇫🇷
- AI-Based IoT Threat Detection & Response
- Federated Learning for Distributed Security
- Adversarial AI & Robustness
- Blockchain-Secured IoT Architectures
- Edge AI Cybersecurity & Inference
- IoT Malware Detection & Analysis
- Digital Twin Resilience & Simulation
- Explainable AI for Security (XAI-Sec)
- Autonomous Security Systems & SOAR
- Secure IoT Data Lifecycle & Governance
- Network Anomaly Detection & SIEM
- 5G/6G Security & Smart Infrastructure