Aymeric Blot – PhD student at Université de LilleEx- civil
Transcription
Aymeric Blot – PhD student at Université de LilleEx- civil
Aymeric Blot PhD student at Université de Lille Ex- civil servant student at ENS Rennes Í B [email protected] http://perso.eleves.ens-rennes.fr/~ablot481/ Born on December 14th, 1991 Education 2015 M.Sc. in Computer Science, École Normale Supérieure de Rennes, Rennes, cum laude. Last year spent in University of British Columbia (Vancouver BC, Canada) 2014 M.Sc. in Computer Science, Université de Rennes, Rennes, cum laude (20th/44). 2012 B.Sc. in Computer Science, École Normale Supérieure de Cachan – Antenne de Bretagne, Rennes, magna cum laude. 2009–2011 MPSI-MP*, Lycée Blaise Pascal, Orsay. Two year intensive course preparing for the competitive entrance examinations to the French Grandes Écoles 2009 Baccalauréat Scientifique, Lycée Blaise Pascal, Orsay, cum laude. Experience 2015-2018 PhD student, Université de Lille – CRIStAL – INRIA Lille-Nord Europe, Lille, France. PhD on multi-objective autonomous systems, DOLPHIN team-project 2014-2015 Trainee, University of British Columbia, Vancouver BC, Canada. 10 month intenship under Prof. Holger Hoos supervision, on automatic algorithm configuration in single- and multi-objective 2014 Trainee, INRIA Lille-Nord Europe, Lille, France. 6 month internship in the Dolphin research group, on multi-objective local searches algorithms and fitness landscapes analysis 2013 Trainee, Shinshu University, Nagano, Japan. 16 week internship under Prof. Hernán Aguirre supervision, on multi-objective local searches algorithms 2012 Trainee, INRIA Lille-Nord Europe, Lille, France. 6 week internship in the Dolphin research group, on single-objective fitness landscapes analysis Publications A. Blot, H. Aguirre, C. Dhaenens, L. Jourdan, M.-É. Marmion, and K. Tanaka. Neutral but a winner! How neutrality helps multiobjective local search algorithms. In Evolutionary Multi-Criterion Optimization (EMO), 2015. M.-É. Marmion, A. Blot, L. Jourdan, and C. Dhaenens. Neutrality in the graph coloring problem. In Learning and Intelligent OptimizatioN Conference (LION7), 2013. Computer skills Languages OCaml, Ruby, Unix Shell, C, C++, Java, R, Python, Lisp Environnement GNU/Linux (archlinux) Misc. emacs, LATEX, beamer, make Languages French English German Japanese Native speaker Fluent Proficient Notions Interests Sport Tennis, badminton Music Piano Misc. Reading, tabletop games TOEIC 2012 score: 985/990 High school level Beginner