Lénaïg Cornanguer is a post-doctoral researcher. Her main research interests are causal inference, discovery of temporal logic from observational data, and explainable anomaly detection.
Lénaïg pursued her PhD at IRISA in Rennes, obtaining her degree from the Université de Rennes 1 for her dissertation titled 'Timed Automata Learning from Time Series' in November 2023. Prior to that, she obtained her Master's of Science in Data Science from the Agrocampus Ouest Engineering School in Rennes, France.
2026 | |
Causal Discovery from Interval-Based Event Sequences. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2026. (oral presentation, 5% acceptance rate; 17.6% overall) |
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2025 | |
TADAM: Learning Timed Automata from Noisy Observations. In: SIAM International Conference on Data Mining (SDM), pp 114-123, SIAM, 2025. (26.7% acceptance rate) |
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SpaceTime: Causal Discovery from Non-Stationary Time Series. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp 19405-19413, AAAI, 2025. (23,4% acceptance rate) |
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