Emmanuel Kieffer
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| Fakultät oder Zentrum | Fakultät für Naturwissenschaften, Technologie und Medizin | ||||
| Department | Fachbereich Informatik | ||||
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Université du Luxembourg Maison du Nombre 6, Avenue de la Fonte L-4364 Esch-sur-Alzette |
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| Büroadresse | MNO, E04 0445-060 | ||||
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| Telefon | (+352) 46 66 44 5309 | ||||
| Fax | (+352) 46 66 44 35309 | ||||
Emmanuel Kieffer is currently research scientist at the University of Luxembourg. He has recently completed his PhD titled “Co-evolutionary Hybrid Bi-level Optimization” at the University of Luxembourg under the supervision of Prof. Pascal Bouvry who is the head of the Parallel Computing & Optimization Group.. His PhD researches were dedicated to the design and resolution of bi-level optimization problems. Prior to that he completed a Master’s in Computer Science with first class honors at the University of Lorraine.
He also received from the University of Lorraine :
- The Master Degree in "Informatique et Décision" (Decision-Support Computing) in 2014
- The Bachelor Degree in "Informatique" (Computer Science) in 2012
- The Technology University degree in "Statistique et Informatique Décisionnelle" (Business-Intelligence) in 2011
In 2016, Emmanuel obtained the certificate "Smart ICT for Business Innovation" from the University of Luxembourg.
His primary research interests include mathematical optimization, evolutionary computing and data-mining.
Languages:
French - English - German
Last updated on: Dienstag, den 27. Oktober 2020
2020
Tackling Large-Scale and Combinatorial Bi-Level Problems With a Genetic Programming Hyper-Heuristic; ; ; ;
in IEEE Transactions on Evolutionary Computation (2020), 24(1), 44--56
Evolving a Deep Neural Network Training Time Estimator; ; ; ; ; ;
in Communications in Computer and Information Science (2020, February)
Bayesian optimisation to select Rössler system parameters used in Chaotic Ant Colony Optimisation for Coverage; ; ; ;
in Journal of Computational Science (2020), 41
2019
A GP Hyper-Heuristic Approach for Generating TSP Heuristics; ; ; ;
in 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019) (2019, May 20)
GP hyper-heuristic for the travelling salesman problem; ; ;
Scientific Conference (2019, January 29)
Tackling Large-Scale and Combinatorial Bi-level Problems with a Genetic Programming Hyper-heuristic; ; ;
in IEEE Transactions on Evolutionary Computation (2019)
Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection; ; ; ; ; ;
in Foundations of Computing and Decision Sciences (2019)
Automatic Software Tuning of Parallel Programs for Energy-Aware Executions; ; ; ;
in Proc. of 13th Intl. Conf. on Parallel Processing and Applied Mathematics (PPAM 2019) (2019, December)
2018
A Competitive Approach for Bi-Level Co-Evolution; ; ;
in 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (2018, May 25)
Bayesian optimization to enhance coverage performance of a swarm of UAV with chaotic dynamics; ; ;
Scientific Conference (2018, February 26)
Visualizing the Template of a Chaotic Attractor; ; ; ; ; ;
in 26th International Symposium on Graph Drawing and Network Visualization (GD 2018) (2018)
Clustering approaches for visual knowledge exploration in molecular interaction networks.; ; ; ;
in BMC bioinformatics (2018), 19(1), 308
2017
A new modeling approach for the biobjective exact optimization of satellite payload configuration; ; ;
in International Transactions in Operational Research (2017)
Bayesian Optimization Approach of General Bi-level Problems; ; ;
in Proceedings of the Genetic and Evolutionary Computation Conference Companion (2017)
2016
Co-evolutionary approach based on constraint decomposition; ; ;
in Co-evolutionary approach based on constraint decomposition (2016, October)
Hybrid mobility model with pheromones for UAV detection task; ; ;
in Hybrid mobility model with pheromones for UAV detection task (2016)
A Novel Co-evolutionary Approach for Constrained Genetic Algorithms; ; ; ;
in Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion (2016)
2014
Bi-objective Exact Optimization of Satellite Payload Power Configuration; ; ; ;
in VIII ALIO/EURO Workshop on Applied Combinatorial Optimization (2014, December)
Multi-Objective Evolutionary Approach for the Satellite Payload Power Optimization Problem; ; ; ; ;
in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2014) (2014, December)
Bi-objective Optimization of Satellite Payload Power Configuration; ; ; ;
in International Conference on Metaheuristics and Nature Inspired Computing (META 2014) (2014, October)
