About
Karim LABADI obtained the HDR Degree (Habilitation to Supervise Research) from the University of Cergy-Pontoise (UCP 2018), and the National Scientific Qualification for Full Professor Degree in "Computer Engineering, Automation and Signal Processing (CNU Section 61 - France). He obtained his Ph.D Degree in Industrial Engineering and Optimization from the University of Technology of Troyes (UTT 2005) with the National Scientific Qualification as Associted Professor in "Computer Engineering, Automation and Signal Processing since 2006 (CNU Section 61 - France) and his M.Sc. Degree (D.E.A) in Applied Automation and Computer Sciences from the Ecole Centrale de Nantes (ECN 2002), after his Engineer Diploma (1998) in Automation and Control Sciences. From 2002 to 2006, he was researcher and teacher member of the Charles Delaunay Institute (ICD CNRS) at the University of Technology of Troyes (UTT), and member of the Optimization of Industrial Systems Laboratory (LOSI). Since 2006, he joined ECAM-ECAM, Graduate School of General Engineering, and becomes permanent member of the Quartz Laboratory (EA 7393 France). He is the author of about 100 papers in international journals, books and international conferences related to modeling, control, performance evaluation and optimization of complex dynamic systems, with real-life applications in Production, Logistic and Urban Mobility. He obtained the 2015 Steffan Schwarz Prize for best scientific work at the European Conference ECEC '2015 (22nd European Concurrent Engineering Conference, April 27-29, 2015, IST, Lisbon, Portugal), and the Best Paper Award of 2022 ICISA Conference on Intelligent Systems and Applications, MITWPU, Pune, India, May 4-6, 2022. He serves or served as scientific and/or organizer member of several international conferences (CoDiT, ICALT, CIAM, EVF, CIE, CISA, ....), and as referee/reviewer for several international journals (IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Intelligent Transportation Systems, Transportation Research, Journal of Control Engineering Practice, …). He served as Advisory Board Member of the “International Journal of Transportation and Logistics (JTL), and as Editorial Board Member of the “International Journal of Logistics and Supply Chain Management” (ISSN 0974-7206), and the “International Journal of Operations System and Human Resource Management” (ISSN 2277-6095). In addition to his teaching and research activities, Prof. LABADI holds or has held several positions of responsibility at ECAM-EPMI such as: From 2013 to 2016- Head of the Production Laboratory (Industrial Automated Platform); From 2010 to 2021 - Research & Doctoral Training Manager - attached to the Scientific Department (R&D coordinator, Scientific and Laboratory Advisor, Head of the LR2E laboratory - Research laboratory in Industrial and Energy Eco-Innovation). Finally, since 2019, he serves as the Head of the Industry and Logistics Department consisting of managing two Engineering specialties, namely MPI (Mechatronics and Industrial Production) and LGA (Industrial Logistics and Purchasing), and as the Head of Engineering Cycle in "Energy & Data" since 2022.
Employment
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ECAM-EPMI Head of Engineering Cycle in "Energy & Data"2022 - Present
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ECAM-EPMI Head of Industrial & Logistics Engineering Division2019 - Present
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ECAM-EPMI Full Professor (Ph.D - HDR) CNU 612006 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (58)
- A Semi-Supervised SVM-Firefly Hybrid for Rainfall Estimation from MSG Data Save
- Hybrid RF–ConvLSTM Approach for Rainfall Estimation from MSG Data over Northern Algeria Save
- Artificial Intelligence for Satellite Image Processing: Application to Rainfall Estimation Save
- Classification of Precipitation Intensities from Remote Sensing Data Based on Artificial Intelligence Using RF Multi-learning Save
- Optimization of Rainfall Intensities Classification Based on Artificial Intelligence Using Recurrent Neural Network Save
- Application of Dempster-Shafer theory for optimization of precipitation classification and estimation results from remote sensing data using machine learning Save
- A Petri Nets-Based Simulation Methodology for Modular Modeling and Performance Evaluation of Car-Sharing Networks Save
- Energy optimization and predictive maintenance of an asphalt plant: A case study Save
- Extreme Learning Machine versus Multilayer perceptron for rainfall estimation from MSG Data Save
- Optimization of One versus All-SVM using AdaBoost algorithm for rainfall classification and estimation from multispectral MSG data Save