Stéphane Bond, M.Sc.

Solution Architect

Stéphane Bond
Team: Emerging Technologies and Data Science

T 514 840-1235, ext. 5404
@ stephane.bond@crim.ca

(M.Sc., computer science, UQAM, 2008 and B. Computer Science and Software Engineering, UQAM, 2004)

Stéphane Bond holds the position of solution architect in CRIM’s Emerging Technologies and Data Science team. He mainly oversees the management and realization of the research and development mandates for various clients in addition to the counseling, support, development and technological watch activities.  He has served as head of project and principal developer for the Solutionneur, a scheduling and timetabling program intended for Québec secondary schools that has been rewarded with an OCTAS 2010 prize.

Stéphane holds a master’s degree in Computer Science, specialized in Software Engineering. He has over a decade of experience in several fields, including programming, software architecture, computer services management and systems integration. Prior to joining CRIM in the fall of 2005, Stéphane had held several positions, including programmer and analyst at the Laval School Board where he notably contributed to the realization of project Mille (an infrastructure model of open source software in education). His main fields of interest are : application architecture, software engineering, optimization techniques based on metaheuristics, enterprise portals, open source software and Web standards.

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Recent news

  • Le CRIM en chiffres
    20/07/2018

    Indicateurs clés de l'année 2017-18.

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Upcoming event

  • IGARSS 2018
    27 July 2018 8:30
    Valence, Espagne
    The 2018 IEEE International Geoscience and Remote Sensing Symposium will take place from July 23-27, 2018 in Valencia, Spain.
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  • Roger Léger RT @LegerRoger: Infolettre Juillet 2018 - Le virage numérique ne prend pas de vacances! - https://t.co/2lfyAoC1zi
  • Tom Landry RT @Tom_Landry_: Thanks to @ouranos_cc , @giz_gmbh , DKRZ and @NRCan for a highly appreciated contribution and collaboration.

Recent Publications

  • Towards Automatic Feature Extraction for Activity Recognition from Wearable Sensors: A Deep Learning Approach

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  • État des lieux des technologies web

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