جست‌وجوی استاد و پژوهشگر

Bastien CAZAUXمشاهده پروفایل

مدرس

• Bioinformatics
• Algorithms
• Genome Assembly
• +۳ مورد دیگر

Bastien CAZAUX is a Lecturer affiliated with ESPRIT, located at Office S3.49 in Scientific City. His research focuses on bioinformatics algorithms, computational genomics, and data compression techniques. Role: Lecturer at ESPRIT Location: Office S3.49, Scientific City Team: Bonsai His research interests span bioinformatics, algorithms, genome assembly, and graph-theoretic approaches to genomic data processing. Key contributions include work on de Bruijn graphs, k-mer indexing, and efficient compression methods for biological sequences. Recent publications highlight trends in pan-genomic analysis , motif discovery , sequence alignment , and graph-based genome representation . These works often combine algorithmic innovation with practical applications in genomic data processing. He is associated with the Bonsai research team, contributing to foundational work in computational biology and algorithm design.

• Network Science
• Data Science
• Complex Networks
• +۳ مورد دیگر

Artur Ziviani is a Senior Researcher at the Data Extreme Lab (DEXL) of the National Laboratory for Scientific Computing (LNCC), a research unit under Brazil's Ministry of Science, Technology, and Innovation (MCTI). He coordinates LNCC's Multidisciplinary Graduate Program in Computational Modeling (M.Sc./Ph.D.). With a Ph.D. from Université Pierre et Marie Curie (Paris 6) and a B.Sc./M.Sc. from Federal University of Rio de Janeiro (UFRJ), he has held visiting positions at INRIA (France) and taught at Paris 6. His research focuses on network science, data science, and interdisciplinary applications, including complex networks, machine learning, and mobility analysis. He is a Senior Member of IEEE and ACM, and an Affiliated Member of the Brazilian Academy of Sciences (2013-2017). His work spans algorithmic information theory, network centrality, and human-aware communication strategies. Recent projects include mobility modeling, protein interaction networks, and biodiversity informatics. Education: Ph.D. (Paris 6, 2003), M.Sc. (UFRJ, 1999), B.Sc. (UFRJ, 1998). Research interests include network characterization, data-driven modeling, and applications in healthcare and biodiversity. His publications analyze network structures, centrality metrics, and spatiotemporal data, with contributions to IEEE, ACM, and Elsevier journals. He also leads initiatives on SDN architectures for high-performance computing and collaborative learning platforms. Awards include recognition as an IEEE Impact Creator and senior fellowships. His team works on projects like SafeCityMap (mobility during pandemics) and MobHet (heterogeneous mobility prediction). He serves on editorial boards for Computer Networks and IEEE Communications Surveys.

Juan A. Fraireمشاهده پروفایل

استاد مهمان

• Space Networking
• Deep-Space Informatics
• Satellite Communications
• +۴ مورد دیگر

Dr. Juan A. Fraire is a researcher at INRIA (France) and serves as a guest professor at Saarland University (Germany) and CONICET-UNC (Argentina). His core research focuses on near-Earth and deep-space networking, with over 100 publications in top journals and conferences. He co-founded and chairs the Space-Terrestrial Internetworking Workshop (STINT) and collaborates with space agencies (NASA, ESA, CONAE) and companies (D3TN, Skyloom). Key projects include STEREO (ANR PRCE coordinator), MISSION (MSCA RISE national coordinator), and AI4LFNM (ESA ITT coordinator). His work spans non-terrestrial networks (NTN), satellite IoT, and interplanetary routing. Research interests emphasize scalable space networking protocols, delay-tolerant networks (DTN), and optical/satellite communication systems. He leads initiatives in autonomous laser link scheduling for Mars exploration, constellation design for global IoT coverage, and hybrid RF/optical terminals for improved pointing accuracy. Over a decade of funding includes European and national grants, focusing on network emulation, edge computing orchestration, and resilient space communication. Dr. Fraire supervises multiple PhD candidates, co-supervising with experts like Prof. H. Hermanns and Prof. H. Rivano. His advising emphasizes interdisciplinary approaches to space informatics challenges. Recent work explores AI-driven congestion control, LoRaWAN scalability for direct-to-satellite IoT, and integrated space-terrestrial cloud latency optimization.

Yezekael HAYELمشاهده پروفایل

پژوهشگر

• Complex Systems Optimization
• Network Science
• Applied Mathematics
• +۶ مورد دیگر

Yezekael HAYEL is a Researcher at the Laboratoire d'Informatique Avignon (LIA) and Director of the Agrosciences & Sciences Doctoral School at Avignon Université. His research focuses on optimizing complex systems with network structures, bridging computer science, applied mathematics, and social sciences. Key areas include opinion dynamics in social networks, cybersecurity, and infrastructure optimization for electric vehicles. He co-authored several influential articles on crowdfunding dynamics, epidemic control, and smart charging algorithms. As Doctoral School Director, he oversees interdisciplinary programs spanning biology, STAPS, computer science, and agricultural sciences. His leadership in the IMPLANTEUS university research school highlights his commitment to multidisciplinary collaboration. Recent work includes a CNRS-published article on opinion evolution models and a collaboration with the Nancy Automation Research Center. Education: Multidisciplinary background in mathematics and computer science Key Projects: ANR-funded IMPLANTEUS research school Optimization of EV charging ecosystems Cybersecurity strategies against network epidemics His pedagogical contributions include teaching at New York University and advocating for international academic exchange. He emphasizes perseverance and creativity in research, advising students to embrace curiosity amid challenges. Awards: None explicitly mentioned, but his leadership roles reflect institutional recognition. Labs/Teams: Active in Avignon Université's Metaboscope Platform and DARI department, collaborating with industry partners like the Nancy Automation Research Center.

Andrea Cozzaمشاهده پروفایل

استاد

• Electromagnetic Engineering
• Signal Processing
• Reverberation Chamber Applications
• +۳ مورد دیگر

Andrea Cozza is a Professor at the University of Paris, leading research in the Electrical and Electronic Engineering of Paris department. Her work focuses on electromagnetics, signal processing, and reverberation chamber applications. She specializes in time reversal techniques for fault detection, antenna measurement, and field synthesis. Key research areas include improving chamber efficiency through advanced stirring methods and analyzing energy distribution in complex media. Dr. Cozza has authored over 50 publications, including seminal works on time-reversal imaging , soft-fault localization in cables , and statistical modeling of reverberation chambers . Her patents cover novel measurement systems and methods for generating uniform electromagnetic fields. Notable contributions include the development of the TREC (Time-Reversal in Reverberation Chambers) framework for optimizing radiated stress testing. Her research emphasizes practical applications in wireless communications, antenna testing, and material characterization. Collaborations with industry partners highlight her expertise in bridging theoretical electromagnetic principles with real-world engineering challenges.

• Energy-Efficient Buildings
• Building Simulation
• Occupancy Modeling
• +۴ مورد دیگر

Abhinandana Boodi is a Researcher-Lecturer at CESI LINEACT, affiliated with the UBO/UMR CNRS 6027 IRDL. They hold a PhD in Energy-Efficient Buildings from the Université de Bretagne Occidentale (2021) and a Master's in Smart Grids and Smart Buildings from Grenoble INP – ENSE3 (2017). Their academic roles include teaching Thermodynamics, Electrical Circuits, and Applied Mathematics to engineering students and master’s programs. Research focuses on building simulation, energy management, and occupancy modeling, with applications in HVAC control, intelligent buildings, and artificial intelligence. Key projects involve hybrid dynamic modeling for energy autonomy and multi-objective optimization in nanogrid buildings. They supervise five PhD students exploring topics like energy autonomy, occupancy prediction, and indoor air quality in healthcare facilities. Publications (2018–2024) emphasize machine learning for occupancy prediction, thermal network models, and reinforcement learning in HVAC control. They are a member of CESI LINEACT and IRDL since 2017, contributing to collaborative research on smart energy systems.

• Predictive Maintenance
• Web Services
• Machine Learning
• +۳ مورد دیگر

DAAJI Marwa is a Researcher-lecturer at CESI, based at the Pau campus. She holds a PhD in Computer Science from the Faculty of Sciences of Tunis (2021) and an Engineering degree from the High Institute of Art and Multimedia of Manouba (2015). Her research focuses on predictive maintenance, web service defect prediction, and machine learning applications in software engineering. Her educational activities include undergraduate teaching in Computer Science, specifically Web Development. Key research contributions include work on BPEL process defect prediction using evolutionary algorithms, multi-criteria web service selection, and formal concept analysis for interface decomposition. PhD Thesis: "Web service interfaces decomposition based on formal concept analysis, design anti-pattern detection and correction using machine learning and genetic algorithms" Engineering Degree Thesis: "Method for generating consensual association rules based on Formal Concept Analysis" Her publications span IEEE conferences and ACM Transactions, with emphasis on combining formal methods with machine learning for software quality improvement. She is affiliated with the Engineering and Numerical Tools research team at CESI.

• Robotics Localization
• Signal Processing
• Machine Learning
• +۳ مورد دیگر

DING Yuehua is a Researcher-Lecturer at the CESI Strasbourg Campus, part of the Engineering and Numerical Tools research team. They hold a HDR (Habilitation à Diriger des Recherches) from the University of Nantes (2020) and a PhD in 2011 focused on MIMO communication system performance optimization. Their academic roles include teaching Electronics, Signal Processing, and Big Data to engineer students in their first and third years. Research interests span Robotics Localization , Data Processing/AI , and Signal Processing , with a focus on integrating machine learning into robotics and wireless communication systems. Recent work emphasizes indoor robot localization using WiFi-visual fusion and SAR-based ship detection. Key technological skills include Python, C, and MATLAB. Publications reflect a strong emphasis on multi-scale object detection, hybrid modeling in marine science, and advanced signal processing techniques for MIMO systems. Review activities include IEEE TSP and TVT. No notable scientific awards are listed, but ongoing contributions include cross-disciplinary projects in medical robotics and materials science.

• Parallel and Distributed Computing
• High Performance Computing
• Edge-Cloud Computing
• +۳ مورد دیگر

Overview Dr. Jean-François DOLLINGER is a Researcher-Lecturer at CESI LINEACT (Strasbourg campus), affiliated with the Engineering and Numerical Tools research team. His academic roles include teaching Computer Science courses (undergraduate/graduate) and supervising student projects in algorithmics, programming, databases, and networks. Education: PhD in Computer Science (2011-2015), University of Strasbourg - ICube Lab MSc in Computer Science (2009-2011), University of Strasbourg (Highest Honors) BSc in Computer Science (2008-2009), University of Strasbourg (Honors) Research Interests: Focuses on edge-cloud computing, high-performance distributed systems, combinatorial optimization in IoT networks, and smart city infrastructure. Specializes in optimizing federated learning, WSN deployment strategies, and hybrid CPU/GPU execution frameworks. Advising & Collaboration: Supervises PhD/Master’s students (e.g., A. BAAHMED on federated learning, K. BOUHOUCH on OpenStack edge deployment) Collaborated with Indonesian universities (Mercu Buana) on RPL protocol extensions Research Team: Leads the Engineering and Numerical Tools group, developing frameworks for edge-cloud infrastructures and BIM-based WSN deployments in smart buildings.

• Data Mining
• Big data
• Fuzzy Clustering
• +۱۰ مورد دیگر

HINDAWI Mohammed is a Researcher-Lecturer at CESI (France) specializing in Computer Science with a focus on Data Mining, Big Data, and Machine Learning. He holds a PhD in Computer Science from INSA Lyon (2013) and teaches at the engineering level. His current research emphasizes Dimensionality Reduction in semi-supervised learning and frugal/embedded AI applications. Education: PhD in Computer Science (2013), INSA Lyon MSc in Knowledge and Decision (2008), INSA Lyon BSc in Software Engineering (2005), Aleppo University Research interests include semi-supervised learning, feature selection, ensemble methods, and clustering techniques. He leads the Engineering and Numerical Tools research team and contributes to the Advanced Automation: AI and Data Science group. His work addresses practical applications like patient monitoring via machine learning and battery state estimation. Publications span over 15 peer-reviewed articles in journals like Knowledge and Information Systems (KAIS) and conferences such as IEEE MMSP and ACM CIKM. He supervises PhD students like Trésor Yao Koffi and collaborates on projects involving embedded systems and healthcare tech.

• Electrical Engineering
• Energy Management
• Artificial Intelligence
• +۴ مورد دیگر

IHSANE Imane is a Researcher-Lecturer affiliated with CESI Saint-Nazaire Campus, France. They are part of the Engineering and Numerical Tools research team and hold a PhD in Electrical Engineering from Nantes University (2020). Their academic background includes a Master's in Electronics, Electrical Engineering, and Automation (University of Picardie Jules Verne, 2014) and a Bachelor's in Industrial Computing (Faculty of Science and Technology, Marrakech, 2012). Research interests focus on Electrical Engineering , Energy Management , and Smart City technologies. Key areas include demand response systems, electrical energy forecasting, and AI-driven optimization for residential and commercial energy consumption. They have supervised international master’s research projects at Polytech Nantes, including work on energy management systems in smart buildings. Publications span topics like multi-objective optimization for demand forecasting (2021), novel evaluation metrics for residential energy analysis (2018), and real-time appliance management models (2017). Their work emphasizes practical applications in smart grids and sustainable energy systems. No scientific awards are listed. Teaching activities include problem-based learning and project pedagogy across associate’s, bachelor’s, and master’s programs in engineering disciplines. They have designed educational content in renewable energy, industrial computing, and thermal systems.

• Energy Performance of Buildings
• Smart Building Systems
• Data Analysis & Sensor Fusion
• +۳ مورد دیگر

MICHENEAU Kevin is a Researcher-Lecturer at CESI LINEACT, affiliated with the Engineering and Numerical Tools Research team. His work spans both applied engineering and fundamental physics research. He holds a PhD in Particle Physics from the University of Nantes (2018) and a Master's in Subatomic Physics from the same institution (2014). His research focuses on energy performance optimization in smart buildings, intelligent building control systems, and data fusion techniques for occupancy modeling. Concurrently, he continues contributions to dark matter detection through advanced analysis of XENON experiment data. Education: PhD in Particle Physics, University of Nantes (2018) Master's in Subatomic Physics, University of Nantes (2014) Research Interests: Developing models for occupancy-aware energy systems Optimizing multi-objective control strategies for building HVAC systems Data-driven approaches for sensor fusion and anomaly detection Continued dark matter research via XENON collaboration experiments Recent Research Trends: Recent work demonstrates a strategic shift toward applied building systems research while maintaining expertise in particle physics. 2024's multi-objective MPC study represents his growing focus on practical energy efficiency solutions, while XENON1T/XENON100 analyses (2017-2019) highlight sustained contributions to dark matter detection methodologies. Grants & Advising: Supervising PhD candidate Adrien BOURGOIN (2023-2026) Laboratory Affiliations: Core member of CESI LINEACT's Engineering and Numerical Tools Research team, collaborating on smart building instrumentation and computational modeling projects.

• Production scheduling
• Supply chain management
• Operational research
• +۳ مورد دیگر

Nouinou Hajar is a Researcher-Lecturer at CESI, affiliated with the Engineering and Numerical Tools research team. She holds a PhD from the University of Technology of Troyes (2021) and degrees in Industrial Engineering and Logistics from the National School of Applied Sciences (ENSA) and University of Lorraine (2018). Her research focuses on production scheduling, supply chain optimization, operational research, and energy-efficient manufacturing systems. She teaches courses on object-oriented programming, algorithms, and production systems modeling for engineering and master's students. Her work integrates Industry 4.0 technologies into manufacturing processes, particularly in textile industries, emphasizing smart scheduling and renewable energy utilization. She advises PhD candidates and supervises internships on topics like energy-flexible production systems and pricing strategies in on-demand manufacturing. Recent publications address semi-online scheduling algorithms, production-transportation coordination, and textile 4.0 frameworks. Her teaching modalities include active pedagogy, lectures, and hands-on sessions (TP/TD) across all engineering program years and master's levels. Research collaborations span renewable energy integration, sustainable supply chains, and decision-making models under Industry 4.0 paradigms.

Sorokhaibam KHABAمشاهده پروفایل

استادیار

• Lean Production
• Sustainable Supply Chain Management
• Sustainable Operations Management
• +۳ مورد دیگر

Sorokhaibam KHABA is an Assistant Professor of Supply Chain Management and Logistics at EM Normandie since 2024. He holds a PhD in Operations and Supply Chain Management from IIT Dhanbad (2018). His research focuses on Lean Production, Sustainable Supply Chains, Industry 4.0, and operational efficiency in mining industries. He has served in accreditation committees (AACSB, IACBE) and engaged in UN SDG-aligned community programs. Education: PhD (2018) from IIT Dhanbad. Previous roles include Assistant Professorships at Institute of Management Technology Dubai (2019-2024) and Lovely Professional University (2018-2019), plus Visiting Professorships in Mexico and India. He actively participates in academic conferences, presenting on topics like quantum computing in logistics, IoT barriers in SMEs, and 3D printing pricing strategies. Research interests span lean methodologies in mining, sustainable practices, and emerging technologies in supply chains. His articles analyze barriers to lean adoption, IoT implementation challenges, and food waste behavior. He co-authored works on RFID in supply chains, SWOT analysis of coal mining, and ethical green procurement in automobiles. Professional contributions include organizing conferences and publishing in journals like TQM Journal and Benchmarking: An International Journal. He emphasizes bridging theory with practical applications in emerging markets, particularly through community outreach and UN SDG initiatives.

Roya TATمشاهده پروفایل

استادیار

• Supply Chain Management
• Sustainability
• Supply Chain Coordination/Contract Design
• +۱ مورد دیگر

Roya TAT is an Assistant Professor in Supply Chain Management at EM Normandie since 2024. Previously, she served as an Associate Professor at ESC Clermont Business School (2023-2024) and completed a Post-Doctorate in Operations Management at IESEG School of Management (2021-2022). She holds a PhD in Industrial Engineering from the University of Tehran (2020) and a Post-Doctorate from IESEG School of Management. Her research focuses on Supply Chain Management, Sustainability, Contract Design, and Operations Management, emphasizing sustainable practices in pharmaceutical supply chains and environmental awareness integration. Education Highlights: PhD in Industrial Engineering, University of Tehran (2020) Post-Doctorate in Operations Management, IESEG School of Management (2021-2022) Research Interests: Roya explores innovative approaches to supply chain sustainability, including pharmaceutical waste reduction, contract design for coordination, and environmental policy applications. Her work combines mathematical modeling with real-world supply chain challenges, particularly in healthcare and retail sectors. Publications: Her articles span topics like sustainable pharmaceutical supply chains, cap-and-trade systems, and inventory optimization. Notable contributions include studies on medicine donation schemes and supply chain coordination mechanisms under environmental regulations. Labs/Teams: No specific lab/team affiliation mentioned, but her work aligns with EM Normandie's Supply Chain & Management Digital initiatives.