• Designing a privacy-preserving simulation framework for IoT intrusion detection systems (IDS) using Federated Learning (FL)
• Optimizing decentralized model training across heterogeneous IoT nodes to detect anomalies while minimizing data exposure

• Architected and managed lab virtualization infrastructure using Proxmox VE, OPNsense, and WireGuard VPN

• Orchestrated containerized workloads using Docker and Kubernetes for centralized lab services

• Implemented network security with DMZ segmentation, automated SSL/TLS management, and openLDAP SSO

• Orchestrated multi-user JupyterHub environment for deep learning research with GPU resource allocation

• Architected a high-concurrency, event-driven microservices architecture using Apache Kafka as the message broker, utilizing asynchronous event streams to decouple video ingestion, inference engines, and access control logic
• Engineered a multimodal deep learning pipeline integrating ResNet-based spatial-temporal features and facial emotion recognition, achieving 97% accuracy with optimized inference latency for edge deployment

• Deployed a containerized processing stack using Docker, implementing full-stack observability with Prometheus and Grafana to monitor system health and ensure sub-millisecond latency for near-instantaneous detection

• Designed and taught complete Artificial Intelligence program to 100-200 students
• Covered supervised learning, regression, classification, neural networks, and Generative AI
• Supervised hands-on Python projects, emphasizing practical implementation and ethical AI practices

• Supervised interns in deploying WiFi-Enterprise infrastructure for the lab
• Supported 20-100 users using 802.1X, LDAP authentication, and FreeRADIUS

• Implemented formally verified, context-aware service discovery and collaboration protocols within a middleware for IoT-connected devices
• Enabled self-healing and recovery in distributed environments
• Integrated and deployed facial-recognition-based access control services as part of the Smart Lab project

Teaching Master’s-level laboratory sessions:

• Distributed Algorithms - Implementation of consensus, fault-tolerance, and leader election mechanisms
• Advanced Operating Systems - Process synchronization, concurrency, and inter-process communication

• Assisted in practical sessions (Travaux Dirigés) for the Master’s course: Verification and Validation of Distributed Systems
• Supported students in applying formal verification, model checking, and testing methods to distributed architectures

• Led workshops and events such as DevFest 2021–2022
• Introduced participants to Go, web services, and cloud technologies
• Promoted peer learning and collaboration through interactive, hands-on sessions

• Authors: H. Halladj, A. Bouzenada, D. E. Saidouni, M. R. Bennamoun, and A. Nouari
• Ref: Proceedings of the First International Conference on Smart Applications (ICSA 2025)

• Introduced participants to backend development concepts and modern API design