Jaël Champagne Gareau

Jaël Champagne Gareau

PhD Student of Computer Science

Université du Québec à Montréal

Biography

I am currently a Computer science PhD candidate at Université du Québec à Montréal (UQAM). My Master’s research focused on planning algorithms for electric vehicles (EV) to find the optimal path between two points such that the total journey time (including the travel time, charging time and expected waiting time at the charging stations) is minimized.

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Interests
  • Artificial Intelligence
  • AI Planning
  • Data Structures and Algorithms
  • Theoretical computer science
Education
  • PhD in Computer Science, 2023

    Université du Québec à Montréal

  • MSc in Computer Science, 2019

    Université du Québec à Montréal

  • Certificate in advanced software development, 2017

    Université du Québec à Montréal

  • BSc in Pure Mathematics, 2016

    Université du Québec à Montréal

Recent Publications

(2023). Cache-Efficient Dynamic Programming MDP Solver. Proceedings of the 26th European Conference on Artificial Intelligence.

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(2022). Cache-Efficient Memory Representation of Markov Decision Processes. Proceedings of the Canadian Conference on Artificial Intelligence (Canadian AI 2022).

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(2022). pcTVI: Parallel MDP Solver Using a Decomposition Into Independent Chains. Proceedings of the International Federation of Classification Societies Conference – IFCS 2022.

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(2021). A Fast Electric Vehicle Path-Planner Using Clustering. Proceedings of the International Federation of Classification Societies Conference – IFCS 2019.

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(2021). Fast and Optimal Planner for the Discrete Grid-Based Coverage Path-Planning Problem. Intelligent Data Engineering and Automated Learning – IDEAL 2021.

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(2020). An Energy-Efficient Method with Dynamic GPS Sampling Rate for Transport Mode Detection and Trip Reconstruction. Advances in Artificial Intelligence (Canadian AI 2020).

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(2019). An Efficient Electric Vehicle Path-Planner That Considers the Waiting Time. Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.

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