Introduction and Research Topics
The Computer Science Department at IRIMAS brings together all computer science researchers at the University of Haute-Alsace (UHA). It is organized around three specialized research teams:
OMeGA: Optimization by Metaheuristics, alGorithmics, and modelizAtion.
MSD: Modeling and Data Science.
RT: Networks and Telecommunications
The staff consists of about thirty full-time employees. Geographically, the MSD and OMeGA are based on the Illberg campus at ENSISA in Mulhouse, while the RT is located in Colmar, at the IUT.
Objectives and Unifying Theme
The department has chosen big data as the central focus of its work. In response to the massive increase in data generated by connected environments, our researchers are developing innovative concepts and tools to manage the complexity of today’s systems.
Notre expertise couvre l’intégralité du cycle de vie de l’information :
Acquisition and Transfer: Expertise in networks and telecommunications.
Storage and Processing: Methods of Data Analysis and Mining.
Value Creation: Using artificial intelligence and optimization.
Collaborations and Interdisciplinarity
La structure de l’IRIMAS favorise une forte synergie entre les équipes informatiques, permettant d’aborder des projets de recherche sur un large spectre technologique. Le département est fort de collaborations industrielles et internationales à travers des projets européens, ANR, etc.
The department also maintains close ties with other disciplines at the institute, particularly through collaborations with the departments of Control Engineering (ASI) and Mathematics. This openness is reflected in a strong commitment to cutting-edge programs, such as the Master’s in Mathematical Engineering and Data Science.
The Teams
The research conducted by the MSD team focuses on modeling and data science, with an emphasis on theories and algorithms that enable the extraction of insights from large volumes of data generated by computer systems.
L’équipe OMeGA conçoit des algorithmes d’optimisation hybrides et des solutions de traitement de données géométriques et visuelles pour résoudre des problèmes complexes dans les domaines de l’énergie, de la santé et de l’industrie.
L’équipe RT développe des solutions innovantes pour sécuriser et optimiser les réseaux sans fil, les objets connectés et les systèmes de communication des véhicules autonomes.
Research Activities
No news for now.
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Fed-DCSRW: a privacy-preserving, dynamic client selection framework for heterogeneous federated learning via roulette wheel mechanism (2026) ArticleCluster Computing
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18th International Conference on Computer Supported Education
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Enhanced Energy Delivery in Electric Vehicle Charging Scheduling via Metaheuristic Approaches (2026) ArticleSN Computer Science
Research and Doctoral studies
Approche d’Apprentissage fédéré mutli-objectif : vers une gestion de l’énergie efficiente et adaptative dans les bâtiments intelligents
Aline ABBOUD
Directeur(s) de thèse : Abdelhafid ABOUAISSA - Ahmad SHAHIN
Conception d’un regroupement intelligent et d’une consommation d’énergie équilibrée dans un réseau de capteurs à l’aide de l’apprentissage automatique
Mohammadreza KAGHAZGARAN
Directeur(s) de thèse : Abdelhafid ABOUAISSA - Jaafar GABER
Contributions à l’analyse de séries temporelles de mouvements humains. Applications à l’évaluation d’exercices de rééducation
Maxime Devanne
Approches distribuées pour l’optimisation et la sécurisation des services urbains intelligents
Mohamed El Amine Brahmia
Contact the department
Department Head
Pr Germain FORESTIER
- Send Us a Message
- Téléphone
MSD Team
Pr Jonathan WEBER
- Send Us a Message
- Téléphone
- ENSISA, 12 rue des Frères Lumière, 68093 Mulhouse
OMeGA Team
Pr Lhassane IDOUMGHAR
- Send Us a Message
- Téléphone
- ENSISA, 12 rue des Frères Lumières, 68093 Mulhouse
RT Team
Pr Abdelhafid ABOUAISSA
- Send Us a Message
- Téléphone
- IUT Colmar, 34 rue du Grillenbreit, 68000 Colmar
Colmar University of Technology :
From the Colmar train station:
- Take Line 4 to the Grillenbreit stop.
ENSISA :
From the Mulhouse train station:
- Take bus line 31 or 51 to the University stop, or bus line 21 to the Lumière stop at the top of the campus.
ENSISA :
From the Mulhouse train station:
- Take Tram Line 1 to the Porte Jeune stop,
- then take Tram Line 2 to the Université stop,
- then a 5-minute walk.
Colmar University of Technology :
From Highway A35:
- Take the D201 toward “Rue du Rhin”; the University of Technology is a 5-minute drive away.
ENSISA :
Depuis l’autoroute A36 :
- take Exit 16a,
- Take the D68 toward “Centre”; the campus is a 5-minute drive away.