AI & Machine Learning Foundations
Developing the mathematical and computational foundations that allow machines to learn from data, incorporate physical knowledge, generalize, and make reliable predictions.
Research includes machine-learning optimization, representation learning, scientific machine learning, model discovery, generalization theory, and learning under uncertainty.
Researchers include:
Mariette Awad ·
Joseph Bakarji ·
Ibrahim Issa ·
Maher Nouiehed
Trustworthy AI, Cybersecurity & Privacy
As intelligent systems become embedded in critical infrastructure and everyday technologies, security, privacy, robustness, and trust become central engineering problems.
MSFEA researchers investigate adversarial machine learning, privacy-preserving AI, explainability, AI-enabled cybersecurity, federated learning, secure intelligent systems, and the vulnerabilities of large language models and AI agents.
Researchers include:
Ali Chehab ·
Imad Elhajj ·
Ayman Kayssi ·
Ammar Mohanna ·
Hassan Noura
Language, Generative AI & Intelligent Information Systems
Language models and generative AI are creating new ways for people and machines to interact with information.
Our researchers work on Arabic natural-language processing, large language models, retrieval-augmented generation, intelligent agents, information extraction, explainable AI, and the evaluation and security of generative systems.
Researchers include:
Mariette Awad ·
Ali Chehab ·
Ammar Mohanna ·
Fadi Zaraket
Robotics, Vision & Autonomous Systems
AI allows engineered systems to perceive their surroundings, interpret complex environments, and act with increasing autonomy.
Research at MSFEA spans computer vision, robotic perception, autonomous systems, UAVs, human–robot interaction, intelligent sensing, and AI-assisted control and navigation.
Researchers include:
Daniel Asmar ·
Naseem Daher ·
Imad Elhajj ·
Bilal Kaddouh
Intelligent Communications & Networks
The next generation of communications systems will increasingly learn, adapt, optimize, and respond to their environments.
MSFEA researchers are using reinforcement learning, federated learning, deep learning, and emerging quantum-machine-learning approaches to rethink wireless communications, network operation, edge intelligence, and connected systems.
Researchers include:
Mahdi Chehimi ·
Imad Elhajj ·
Sanaa Sharafeddine
AI for Engineering, Health, Energy, and the Built Environment
Some of the most important opportunities for AI emerge when machine intelligence meets the physical world, including material characterization using machine learning.
Across MSFEA, researchers are applying machine learning to structural health monitoring, biomedical signals, energy systems, environmental sensing, geomechanics, construction, materials, and intelligent devices.
Researchers include:
Hicham Abou Ibrahim ·
Jawad Alami ·
Rabih Jabr ·
Massoud Khraiche ·
Elsa Maalouf ·
Samir Mustapha ·
Darine Salam ·
Issam Srour ·
Karim Zahed