I’m a postdoctoral researcher at Orange Innovation, where I design and deplopy robotic swarm architectures combining multimodal perception, LLM-based reasoning, and AI planning to deliver robust autonomous operation under real-world constraints. Previously, at Télécom SudParis, I led core technical contributions for the PANDORA EU project, where I developed scalable AIoT pipelines including ML-based synthetic data generation, adaptive model selection, and network-aware planning for robotic systems. I’ve obtained my PhD from Institut Polytechnique de Paris (IP Paris) in 2024 with honors.
I build scalable AI systems that enable autonomous decision-making in industrial and distributed environments. My expertise spans self-adaptive systems, AIoT, edge–cloud deployments, and distributed systems. I specialize in turning advanced AI research into deployable, resilient systems that operate at scale.
Professional Experience#
Postdoc Researcher
Nov. 2025–Present
Châtillon, France
- Developing adaptive data fusion techniques combining LLMs and ML models to maximize perception precision across heterogeneous robotic swarm sensors.
- Designing LLM-assisted agentic optimization workflows for 6G industrial IoT communication, translating perception outputs into real-time network decisions via tool-integrated AI agents.
- Leading research for the CANCUN ANR project, enabling efficient and sustainable IIoT communication.
Postdoc Researcher
Jan. 2025–Oct. 2025
Évry, France
- Technical lead and main contributor for the PANDORA EU project for developing scalable, trustworthy, and autonomous AIoT operation.
- Built a causal-GAN synthetic data generation pipeline producing trustworthy, realistic IoT datasets to improve ML model robustness in data-scarce industrial environments.
- Developed an autonomous MLOps framework for adaptive ML model distribution and lifecycle management across heterogeneous Edge-Cloud infrastructures.
- Mentored PhD and MSc researchers in autonomous system design and experimental methodology.
PhD Researcher
Nov. 2021–Dec. 2024
Évry, France
- Developed CRAFTER: a Python/PyTorch causal reinforcement learning system for self-adaptive IoT, reducing response latency by 25% - deployed across a 5-node containerized testbed simulating 100 IoT devices.
- Developed PlanEMQX: an AI planning-enabled MQTT broker for adaptive, priority-aware data flow management, cutting latency by 20% for time-critical flows - Distinguished Artifact Award, IEEE ICSA 2024.
- Designed hybrid AI architecture integrating causal inference, RL, and symbolic planning into a unified self-adaptation middleware - published across 3 A-ranked CORE venues.
- Mentored MSc researchers in autonomous systems and experimental methodology.
R&D Intern
Apr. 2021–Oct. 2021
Évry, France
- Developed a Java-based simulation tool for performance evaluation of IoT data exchange.
- Optimized IoT data flow performance using AI planning methodologies.
Telecom Engineering Intern
May. 2019–Jul. 2019
Beirut, Lebanon
- Conducted network analysis and optimization for telecom infrastructures.
Education#
PhD in Computer Science
2024
Institut Polytechnique de Paris (IP Paris), France
Master's in Computer Science
2021
Lebanese University, Lebanon
Thesis: Designing an Edge-based Data Exchange Infrastructure for Smart BuildingsBachelor of Engineering - Computer Engineering
2020
American University of Beirut, Lebanon
Final Year Project: Instructor’s Problem Set Recycling and Evolving