Chloé Mercier
Présentation
My research lies at the interface between computer science, cognitive science, and the humanities, with a focus on education. I recently completed my PhD with the Mnemosyne team (Inria, LaBRI, IMN, Bordeaux Neurocampus) in partnership with the LINE (Laboratory of Digital Innovation in Education, Université Côte d'Azur, Nice), where I worked on computational models of creative problem solving. My aim was twofold: first, to bridge the gap between educational psychology, learning sciences, and computational neuroscience; and second, to better understand how transversal skills— necessary for adapting in a rapidly changing world —are acquired and developed. Building on this foundation, I am expanding my research to explore how computational models can help create more adaptive, inclusive, and interdisciplinary learning environments, drawing inspiration from embodied cognition and learning principles observed in both natural and artificial systems. I have also recently developed a strong interest in the use of language and creative writing as metacognitive tools for knowledge construction. In this context, I advocate for the STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach, integrating artistic and creative practices into scientific education to encourage deeper engagement and innovation. My personal experience with dance has also shaped my understanding of cognition, movement, and learning, reinforcing my interdisciplinary perspective. I believe that such creative approaches in education and outreach, combined with citizen science and open science initiatives, could help bridging several gaps: the gender gap in STEM, by encouraging more women to engage with the so-called 'hard' sciences, and the gap between science and society by fostering trust, ethical awareness, and a stronger connection between research and real-world ecological and societal challenges.
Publications
Publications
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An Ontology to Formalize a Creative Problem Solving ActivityIEEE Transactions on Cognitive and Developmental Systems, 2022, pp.1-1. ⟨10.1109/tcds.2022.3210234⟩ |
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Learning with immersive technologies : a VR task to study collaborative learningIHM'24 - 35e Conférence Internationale Francophone sur l'Interaction Humain-Machine, AFIHM; Sorbonne Université, Mar 2024, Paris, France |
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Représenter l'apprentissage humain dans des problèmes ouvertsDataquitaine 2023 - IA, Recherche Opérationnelle & Data Science, Kedge Business School Bordeaux, Mar 2023, Bordeaux, France |
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Ontology as manifold: towards symbolic and numerical artificial embeddingWorkshop on VSA and hyperdimensional computing - Winter 2022 session, Luleå University of Technology, Sweden and UC Berkeley, USA, Jan 2022, Virtual, Sweden |
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Formalizing Problem Solving in Computational Thinking : an Ontology approachIEEE ICDL 2021 – International Conference on Development and Learning 2021, Aug 2021, Beijing, China |
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Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embeddingKRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam |
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Reinforcement Symbolic LearningICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava / Virtual, Slovakia |
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The role of cognitive processes in creative problem solving: a computational approach7th annual meeting of the Society for the Neuroscience of Creativity (SfNC 2022), May 2022, Virtual, United States |
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Apprentissage par renforcement sur des connaissances symboliques structurées : modéliser la résolution créative de problèmesCJC-SCo 2022 - Colloque des jeunes chercheur·se·s en sciences cognitives, Apr 2022, Paris, France. |
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Enseigner et apprendre à l'ère de l'intelligence artificielleCanopé, Livre blanc, 2023 |
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Un MOOC pour initier a l'IA : « Intelligence Artificielle avec Intelligence »Canopé. Enseigner et apprendre à l’ère de l’intelligence artificielle, pp.96, 2023 |
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Aha ! Le cri de la créativité2022 |
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Metrizable symbolic data structure for ill-defined problem solving2024 |
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Algorithmic ersatz for VSA: Macroscopic simulation of Vector Symbolic Architecture2024 |
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Deciphering Cognitive Processes in Creative Problem Solving: A Computational ApproachRR-9555, Inria & Labri, Université de Bordeaux. 2024, pp.26 |
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Modeling Creative Problem-Solving Tasks from a Computational and Neuroeducational ApproachRR-9556, Inria & Labri, Univ. Bordeaux. 2024, pp.27 |
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Representation of belief in relation to randomnessRR-9493, Inria & Labri, Univ. Bordeaux. 2022, pp.20 |
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Développement d'une ontologie pour l'analyse d'observables de l'apprenant dans le contexte d'une tâche avec des robots modulaires[Rapport de recherche] RR-9376, Inria. 2020, pp.48 |
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Modeling cognitive processes within a creative problem-solving task : from symbolic to neuro-symbolic approaches in computational learning sciencesTechnology for Human Learning. Université de Bordeaux, 2024. English. ⟨NNT : 2024BORD0065⟩ |