Maëlle Moranges
  • Bio
  • Experience
  • Projects
  • Publications
  • Collective responsibilities
  • Dissemination
  • Teaching
  • Recent & Upcoming Talks
    • Example Talk
  • Teaching Experience
    • Technology Watch
    • Introduction to Machine Learning
    • Graph Data Mining
      • Graph Data Mining (GDM)
    • Language Typology
    • Biostatistics and Bioinformatics
    • Data Mining
    • Knowledge Discovery in Data
    • Advanced Databases
    • Psychophysiology of Perception
    • NeuroConferences
  • Responsabilities
    • Explain’AI Workshop - EGC 2025, Strasbourg
    • Design of the Educational Framework for the Bachelor's Program in AI, Biotech and Health
    • ComSciCon 2024, Lyon – Organizing Team
    • Explain’AI Workshop - EGC 2024, Dijon
    • ComSciCon 2023, Nancy – Organizing Team
    • Scientific Game Jam 2023 – Scientific Mentor
    • ComSciCon 2022, Marseille – Organizing Team
  • Dissemination of Scientific Knowledge
    • 🇫🇷 Sensibilisation aux sciences du numérique au Lycée Simone Weil
    • 🇫🇷 Relecture du script d'une vidéo de vulgarisation scientifique sur la mémoire avec Exaltia
    • 🇫🇷 Animation de la gazette du festival Pop'Sciences
    • 🇫🇷 Rédaction d'articles par mes étudiants sur l'Intelligence Artificielle
    • 🇫🇷 Rendez-vous LYSiERES² sur l’Intelligence Artificielle en santé
    • 🇫🇷 Mini-série animée de Mediasens sur l'olfaction
    • 🇫🇷 Participation à un Cinéma-Débat sur l'Intelligence Artificielle à Belleville-en-Beaujolais
    • 🇫🇷 Ma thèse en 180 secondes ⏱️
    • 🇫🇷 Vidéo de vulgarisation réalisée avec L’Exploratoire 📽️
    • 🇫🇷 Création d'un jeu vidéo lors de la Scientific Game Jam
  • Scientific projects
    • AI for Stroke Outcome Prediction
    • Analysis and Enhancement of a Medical E-Learning Database
    • Leveraging AI to Enhance Educational Practices
    • Exploring the Impact of COVID-19-Related Smell Disorders
    • Tracking Olfactory Disorders as Early COVID-19 Indicators
    • Understanding the Neurophysiological Mechanisms of Olfactory Perception and Emotion Using AI
  • Projects
  • Publications
    • Decoding student learning in medical education through UNESS platform interactions
    • Using Exceptional Attributed Subgraph Mining to Explore Interindividual Variability in Odor Pleasantness Processing in the Piriform Cortex and Amygdala
    • Peripheral Nervous System Responses to Food Stimuli: Analysis Using Data Science Approaches
    • Variabilités émotionnelle et neurophysiologique dans la perception olfactive: étude par l’intelligence artificielle
    • Using subgroup discovery to relate odor pleasantness and intensity to peripheral nervous system reactions
    • Contribution de l’anthropologie sensorielle à l’étude du COVID-19
    • Explicit and implicit measures of emotions: Data-science might help to account for data complexity and heterogeneity
    • Modeling the subjectivity of human olfaction and its variability
    • Recovery from COVID-19-related olfactory disorders and quality of life: insights from an observational online study
    • Exploring the relation between olfaction and affective states using artificial intelligence algorithms
    • Smell and taste changes are early indicators of the COVID-19 pandemic and political decision effectiveness
    • Exceptional attributed subgraph mining to understand the olfactory percept
  • Experience
  • Technology Watch
  • Introduction to Machine Learning
  • Graph Data Mining
  • Language Typology
  • Biostatistics and Bioinformatics
  • Data Mining
  • Knowledge Discovery in Data
  • Advanced Databases
  • Psychophysiology of Perception
  • NeuroConferences

On this page

  • Graph Data Mining (GDM)
Teaching Experience
Graph Data Mining

Graph Data Mining

Graph Data Mining (GDM)

Promotion: ING2 SCIA (20 students) Year: 2022-2023 Institution: EPITA Lyon
Hours: 3h CM, 6h TP Responsibilities: Created a lecture and practical session, supervised projects.
Description: Covered community detection and pattern discovery in graphs. Students participated in a one-day hackathon.

Last updated on Jun 23, 2023
← Introduction to Machine Learning Jun 27, 2023
Language Typology May 29, 2023 →

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