Alaa
DAOUD
-
Bâtiment JONAS
Bureau 208
My research focuses on distributed Artificial Intelligence, particularly Multi-Agent Systems (MAS), and their application to complex and dynamic environments. I am interested in designing decentralized coordination mechanisms that enable autonomous entities to cooperate efficiently in contexts characterized by partial, evolving, and distributed information.
My work mainly addresses intelligent transportation systems, autonomous vehicles, and cyber-physical systems, with a particular focus on dynamic resource allocation, energy management, and collective decision-making. More broadly, I aim to develop robust, explainable, and resource-efficient AI approaches capable of addressing current challenges related to mobility, the Internet of Things, and sustainable transitions.
My scientific approach combines modeling, multi-agent simulation, and experimentation to design solutions that are both theoretically grounded and applicable to real-world problems.
Diplômes universitaires
- 2022 :
PhD in Computer Science – University of Lyon / Mines Saint-Étienne. Dissertation focused on multi-agent coordination for resource allocation optimization in connected autonomous vehicle fleets applied to on-demand transportation systems. Research areas include distributed Artificial Intelligence, Multi-Agent Systems, and Intelligent Transportation Systems.
- 2018 :
Research Master's degree in Computer Science – Cyber-Physical and Social Systems (CPS²), Jean Monnet University / Mines Saint-Étienne. International program focused on Artificial Intelligence, Internet of Things, cyber-physical systems, and smart city and transportation technologies.
- 2015 :
Engineering degree in Information Systems and Software Engineering – University of Damascus, Syria. Training focused on software engineering, databases, information systems, and application development.
Proceedings of International Conference with selection committee
Crinchon M., Daoud A., Adam E., Mandiau R. (2026). ECO-Charge: Multi-Agent Smart-Charging for Electric Vehicles. The 17th International Conference on Ambient Systems, Networks and Technologies (ANT), Istanbul, Türkiye, april .
Daoud A., Alqasir C. (2026). From Consensus to Causality: Adaptive Reliability Fusion for Object Detection Ensembles. The 3rd International Workshop on Causality, Agents and Large Models (CALM-26), In conjunction with The 17th International Conference on Ambient Systems, Networks and Technologies, Istanbul, Türkiye, april .
Seminar and other papers
Crinchon M., Daoud A., Adam E., Mandiau R. (2026). Coordinated Planning for Charging Fleets of Autonomous Electric Vehicles: A Multi-Agent Approach. Journées MAFTEC, ACE/MAFTEC et MAFTEC/SMAA du Groupement de Recherche RADIA (Raisonnement, Apprentissage, et Décision en Intelligence Artificielle), Lyon, France, january .
Crinchon M., Daoud A., Adam E., Mandiau R. (2025). ECO-CHARGE : Optimisation de la recharge d'une flotte de véhicules autonomes, approche décentralisée (SMA). Poster, Journées Francophones sur les Systèmes Multi-Agents (JFSMA), Dijon, France, july .